The Kingdom of Cambodia Nation Religion King 

77777    

National GHG Emissions Inventory Report 

  

Prepare for submission to GSSD  by GDANCP 

 June 2019 

Assignment details

Development of the national greenhouse gas inventory (GHG-I) and the GHG-I and the mitigation actions chapters of the first biennial update report of the Kingdom of Cambodia.

Project: Forest Carbon Partnership Facility II

Prepared by

Contact main author(s)

María José (Pepa) López Juan Luis Martín Etienne Mathias pepa.lopez@gauss-int.com jlm@gauss-int.com etienne.mathias@citepa.org

Date

21 May 2019

TABLE OF CONTENT

Executive summary ........................................................................................ i 

Preface ............................................................................................. 1 

1.  Introduction ................................................................................ 2 

2.  National system ........................................................................... 7 

2.1.  Institutional arrangements for compiling GHG inventory ............................... 7 

2.2.  Inventory planning, inventory preparation and inventory management ........... 10 

Identification of key categories .................................................................................... 10 

Data Collection ....................................................................................................... 11 

Inventory compilation ............................................................................................... 13 

QA/QC Plan .......................................................................................................... 14 

Documentation and archiving ...................................................................................... 16 

3.  GHG emissions inventory – edition 2019 ........................................... 16 

3.1.  Emissions trends (1994-2016) .............................................................. 17 

3.2.  Energy sector .................................................................................. 21 

3.2.1.  Characterization of the sector ............................................................. 21 

3.3.2. Data sources ..................................................................................... 23 

3.3.3. Energy emissions by category ................................................................ 24 

1A1. Energy Industries .............................................................................................. 25 

1A2. Manufacturing Industry and construction .................................................................. 29 

1A3. Transport ....................................................................................................... 32 

1A4. Other ............................................................................................................ 36 

3.3.4. Comparison between the Reference and Sectoral Methods ............................ 40 

3.3.5. Energy emissions trend ........................................................................ 41 

3.3.  Industrial Processes and Product Use (IPPU) sector .................................... 44 

3.4.1. Characterization of the sector ............................................................... 44 

3.4.2. Data sources ..................................................................................... 46 

3.4.3. Industrial emissions by category ............................................................. 46 

2A. Mineral Industry ................................................................................................. 46 

2D1. Lubricants ...................................................................................................... 50 

2F - Substitutes for Ozone Depleting Substances (F-gases) .................................................. 51 

3.4.4. IPPU emissions trends .......................................................................... 54 

3.5. AFOLU sector ....................................................................................... 55 

3.5.1. Characterization of the sector ............................................................... 55 

3.5.2. Data sources ..................................................................................... 55 

3.5.3. AFOLU emissions by category................................................................. 56 

3.A – Livestock ..................................................................................................... 56 

3.A.1 - Enteric Fermentation ..................................................................................... 57 

3.A.2 - Manure Management ..................................................................................... 57 

3.B – Land ........................................................................................................... 59 

3.C.1 - Emissions from biomass burning ..................................................................... 62 

3.C.2 – Liming ....................................................................................................... 64 

3.C.3 - Urea application ........................................................................................... 64 

3.C.4 - Direct N2O emissions from managed soils .......................................................... 65 

3.C.5 - Indirect N2O emissions from managed soils ....................................................... 69 

3.C.6 - Indirect N2O emissions from manure management ............................................... 71 

3.C.7 - Rice cultivation ............................................................................................ 73 

3.D.1 - Harvested wood products ............................................................................... 78 

3.5.4. AFOLU emissions trends ....................................................................... 78 

3.6. Waste sector ........................................................................................ 79 

3.6.1. Characterization of the sector ............................................................... 79 

3.6.2. Data sources ..................................................................................... 80 

3.6.3. Waste emissions by category ................................................................. 80 

4A. Solid waste disposal ............................................................................................ 83 

4B. Biological treatment of waste ................................................................................. 85 

4C. Incineration and open burning ................................................................................ 88 

4D. Wastewater treatment and discharge ........................................................................ 90 

3.6.4. Waste emissions trends ........................................................................ 92 

3.7.  Key category assessment and uncertainty analysis .................................... 94 

3.7.1.  Key category assessment .................................................................... 94 

Level assessment ................................................................................................... 95 

Trend assessment ................................................................................................... 95 

Disaggregation level ................................................................................................ 95 

Results ................................................................................................................ 96 

3.7.2.  Uncertainty analysis ......................................................................... 100 

Energy sector ...................................................................................................... 104 

IPPU sector ......................................................................................................... 105 

Waste sector ....................................................................................................... 105 

AFOLU sector ...................................................................................................... 107 

3.8.  Results of the QA/QC ........................................................................ 108 

Quality Control ..................................................................................................... 108 

Quality Assurance ................................................................................................. 111 

3.9.  Improvement plan ........................................................................... 112 

Energy sector ...................................................................................................... 112 

IPPU sector ......................................................................................................... 113 

AFOLU sector ...................................................................................................... 114 

3.A.1 - Enteric Fermentation ..................................................................................... 114 

3.A.2 - Manure Management .................................................................................... 114 

3.B - Land ........................................................................................................... 114 

3.C.1 - Biomass burning .......................................................................................... 115 

3.C.2 - Liming ...................................................................................................... 116 

3.C.3 - Urea application .......................................................................................... 116 

3.C.4 - Direct N2O Emissions from managed soils ........................................................... 116 

3.C.5 - Indirect N2O Emissions from managed soils ......................................................... 116 

3.C.6 - Indirect N2O Emissions from manure management ................................................. 116 

3.C.7 - Rice cultivations .......................................................................................... 116 

Waste sector ....................................................................................................... 117 

3.10.  Reporting tables .............................................................................. 118 

i

Executive summary Key messages

The 2019 edition of the GHG inventory of the Kingdom of Cambodia includes emissions for the years 1994-2016 of the gases CO2, CH4, N2O and HFC and the sectors of Energy, Industrial Processes and Product Use (IPPU), Agriculture, Forestry and Other Land Use (AFOLU) and Waste.

The inventory has been calculated following the methodologies of the 2006 IPCC Guidelines. The global warming potentials uses are those of the Fourth Assessment Report of IPCC, based on the effects of GHGs over a 100-year time horizon.

The emissions of greenhouse gases estimated for the total of the inventory including Forestry and Other Land Use (FOLU) are 163 882 Gg of CO2-eq for year 2016, which is a 284 per cent higher than emissions in 1994. The main driver for this increase in GHG emissions is the deforestation reflected in the emissions of the FOLU sector.

The major contributor to the GHG emissions during the entire period is the Forest and Other Land Use sector (FOLU), which is driven by the change in carbon stocks due to deforestation and other changes in the land use. The second largest emitter sector in the country is the Agriculture sector. Cambodia has an economy which is strongly marked by the contribution of agriculture to total GDP, and that is also reflected in the emission pattern. In the time span covered by the inventory, Cambodian GDP has experienced a significant expansion, along its population. This is reflected in the increasing trend of the emissions of the third and fourth largest emitter sectors in the country, the Energy and Waste sectors. The small size of the carbon intensive-industrial sector in the country makes the IPPU the fifth contributor the national total GHG emissions.

Emissions (including FOLU) per capita have increased from 4.00 to 10.44 tonnes CO2-eq/ inhabitant/year. This increase is mainly due to the high deforestation produced in the country. Without FOLU, emissions per capita have increased from 1.47 to 2.09 tonnes CO2-eq/ inhabitant/year due to increasing energy consumption and overall activity levels (GDP). Conversely, GHG emissions (including FOLU) per unit of GDP have been reduced from a 15.41 to 8.26 tonnes Co2-eq/thousand USD/year. Without FOLU, emissions per unit of GDP have decreased from 5.65 to 1.66 tonnes Co2-eq/thousand USD/year. This reduction is due to the fact that the expansion of GDP is significantly higher than the increase of GHG emissions.

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1 - Introduction

The 2019 edition of the National Greenhouse Gas (GHG) emissions inventory of the Kingdom of Cambodia covers the GHG emissions of years 1994-2016.

This inventory addresses the estimation of the main direct greenhouse gases: Carbon Dioxide (CO2), Methane (CH4), Nitrous oxide (N2O) and Hydrofluorocarbons (HFC). Due to the lack of information on their occurrence, the emissions of Perfluorocarbons (PFC), Sulphur hexafluoride (SF6) and Nitrogen trifluoride (NF3) have not been estimated. The gases which are considered ozone precursors: carbon monoxide (CO), oxides of nitrogen (NOx), non-methane volatile organic compounds (NMVOCs), and Sulphur dioxide (SO2), which are also reported in national GHG emissions inventories, have not been estimated in an exhaustive manner in all the sectors

Greenhouse gas emission and removal estimates are divided into the main sectors of the 2006 IPCC Guidelines, which are groupings of related processes, sources and sinks:

Energy Industrial Processes and Product Use (IPPU) Agriculture, Forestry and Other Land Use (AFOLU) Waste

Each sector comprises individual categories (e.g., transport) and sub-categories (e.g., cars). A national total is calculated by summing up emissions and removals for each gas.

Overall, the 2006 edition of the IPCC Guidelines has been followed for estimating the GHG emissions and removals of the inventory. For estimating the emissions of precursors, the Guidelines of EMEP/EEA 2016 have been used, as proposed by IPCC.

The activity data used for developing the inventory is mainly the information which is available at national level and was obtained by the inventory coordinator for the different categories of each sector from the national compilation team. Despite the efforts made, the scarcity of data has been the main challenge for developing estimates in all sectors and emission sources and removals.

In the cases in which the information available at national level was not enough for developing estimates in line with the IPCC guidelines, international sources of data have been used and assumptions made using expert judgment.

All sectors include an improvement plan for improving the quality of the inventory in the future. For all sectors the improvement plan is mainly focused on improving the information available from national sources.

2 - Institutional arrangements and the elaboration of the inventory for the Kingdom of Cambodia

The National Council for Sustainable Development (NCSD) is a high-level inter-ministerial mechanism created by the Royal Kingdom of Cambodia to prepare, coordinate, and monitor implementation of policies, strategies, plans and programmes related to sustainable

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development. The NCSD is chaired by minister of environment and is supported by the General Secretariat for Sustainable Development (GSSD). As part of the GSDD, The Department of Climate Change (DCC) is responsible for formulation of draft climate change plans and policies and serves as secretariat to the Cambodian Government’s focal points for UNFCCC, the Intergovernmental Panel on Climate Change (IPCC), the Kyoto Protocol and the Clean Development Mechanism (CDM) and other mechanisms. DCC also coordinates inter-ministerial Technical Working Groups (TWGs) by sectors and themes (GHG inventory, mitigation, vulnerability and adaptation, and UNFCCC implementation). DCC also supports the climate change activities of the NCSD and acts as the coordinating agency for UNFCCC reporting.

Therefore, the NCSD through the GSSD and the DCC have the overall responsibility for the inventory preparation. Nevertheless, Cambodia does not count yet with a sustainable inventory compilation unit or exhaustive institutional arrangements for inventory planning, preparation and management.

For the development of the 2019 edition of the GHG inventory, the GSSD signed a letter of agreement (LoA) with the General Directorate of Administration for Nature Conservation and Protection (GDANCP) of the Ministry of Environment (MoE) to assist the DCC in the preparation of national greenhouse gas inventory and the inventory chapter of the BUR. Thought this letter, the GDANCP has acted as inventory coordinator for the preparation of the 2019 edition of the inventory. The detailed roles and responsibilities for the 2019 inventory development were the following:

Roles and responsibilities for the development of the GHG-I

Role Responsibility

Climate Change lead agency

Validation of results, supervision and strategic oversight

Inventory coordinator Coordinate and oversee the work of international and national consultants.

UNDP coordinator Oversee the work of the international compilers and supports the coordination with the national inventory coordinator.

International inventory compilers

Estimate the GHG emission inventory, perform quality control processes, write the inventory report and provide capacity building to national compilers.

National inventory Compilers

Gathering activity data, supporting the compilation of GHG emissions estimates and perform quality checks in line with the QA/QC plan.

International QA experts

Carry out the quality assurance of the inventory, in line with the QA/QC plan.

Data providers Provide the information available as needed for the development of the national inventory.

3 - Trend of emissions

The emissions of greenhouse gases estimated for the total of the inventory including Forestry and Other Land Use (FOLU) are 163 882 Gg of CO2-eq for year 2016, which is a 284 per cent

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higher than emissions in 1994. The main driver for this increase in GHG emissions is the deforestation reflected in the emissions of the FOLU sector. Without FOLU, the GHG emissions are 32 871 Gg of CO2-eq for year 2016, which is a 110 per cent higher than emissions in 1994.

The next table provides an overview of the emissions of each inventory sector for the years 1994, 2000, 2005, 2010, 2015 and 2016.

Trend of emissions (GHG, Gg CO2-eq)

Inventory Sector 1994 2000 2005 2010 2015 2016

Energy 2690.95 3102.73 3454.41 5306.37 8356.31 9601.61IPPU 3.81 6.04 12.73 492.84 1001.38 821.15 Waste 1756.18 2111.61 2415.89 2633.62 2974.53 3050.67 Agriculture (3A + 3C) 11202.58 13032.31 15336.38 18136.08 18068.35 8397.67

Forest and Other Land Use (FOLU) (3B)

27018.62 27018.62 27018.62 131011.24 131011.24 31011.24

Total (without FOLU) 15653.52 18252.70 21219.42 26568.91 30400.57 32871.10Total (with FOLU) 42672.14 45271.32 48238.04 157580.15 161411.82 63882.35

As illustrated in the following figure, the emissions of all sectors present an increasing trend from 1994 to 2016.

GHG emissions; Years 1994-2016 (Gg of CO2-eq)

The major contributor to the GHG emissions during the entire period is the Forest and Other Land Use sector (FOLU), which is driven by the change in carbon stocks due to deforestation and other changes in the land use.

The second largest emitter sector in the country is the Agriculture sector. Cambodia has an economy which is strongly marked by the contribution of agriculture to total GDP, and that is also reflected in the emission pattern. The main driver for the GHG emissions increase in the

0

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160,000

180,000

Energy IPPU Waste Agriculture FOLU

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agriculture sector is the development of the rise cultivations, whose activity level and emissions increased by a rate of ~2.5 in the period 1994-2016.

In the time span covered by the inventory, Cambodian GDP has experienced a significant expansion, along its population. This is reflected in the increasing trend of the emissions of the third and fourth largest emitter sectors in the country, the Energy and Waste sectors, respectively. The energy demand has experienced a significant increase, transport sector is expanding, and the population is migrating to cities; all these factors combined led to increasing fuel consumption and higher GHG emissions in the energy sector. The increased population and the changes in waste management and sanitation are the main drivers for the emissions of the waste sector.

Last but not least, the small size of the carbon intensive-industrial sector in the country makes the IPPU the fifth contributor the national total GHG emissions. Nevertheless, IPPU sector emissions experienced a growing expansion in the last period of the series, due to the raising contribution of cement production and the consumption of fluorinated gases.

Emissions (including FOLU) per cápita have increased from 4.00 to 10.44 tonnes CO2-eq/ inhabitant/year. This increase is mainly due to the high deforestation produced in the country. Conversely, GHG emissions (including FOLU) per unit of GDP have been reduced from a 15.41 to 8.26 tonnes Co2-eq/thousand USD/year. This reduction is due to the fact that the expansion of GDP is significantly higher than the increase of GHG emissions.

The following figure shows the percentage of emissions of each inventory sector for years 1994 and 2016.

Percentage of emissions by sector (as of % of CO2-eq)

The previous figure shows the decreasing contribution to total national emissions in 2016 compared to 1994 in the sectors of energy, waste and agriculture, and the increase in the contribution of FOLU and IPPU.

In terms of the contribution of each GHG to national total emissions, CO2 is the main gas emitted, driven by the large contribution of the FOLU sector to national total emissions, followed by CH4, N2O and HFC.

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Contribution of each gas to national total emissions with FOLU (%)

Gas 1994 2000 2005 2010 2015 2016

CO2 69.73% 66.49% 63.32% 86.81% 86.81% 86.73% CH4 25.52% 28.55% 31.57% 11.36% 11.30% 11.41% N2O 4.75% 4.96% 5.09% 1.76% 1.69% 1.63% HFC 0.00% 0.00% 0.01% 0.07% 0.20% 0.23%

The following figure provides an overview of the contribution of each sector to national total GHG emissions without considering the FOLU sector.

GHG emissions without FOLU; Years 1994-2016 (Gg of CO2-eq)

The GHG emissions without the FOLU sector are dominated by the contribution of the agriculture sector and the increasing contributions of the energy and waste sectors. In year 2016, the split of emissions without FOLU by sector is the following: Agriculture 56.0%, Energy 29.2%, Waste 9.3% and IPPU 5.5%.

Without FOLU, emissions per capita have increased from 1.47 to 2.09 tonnes CO2-eq/ inhabitant/year due to increasing energy consumption and overall activity levels (GDP). The emissions per unit of GDP have decreased from 5.65 to 1.66 tonnes Co2-eq/thousand USD/year. This reduction is due to the fact that the expansion of GDP is significantly higher than the increase of GHG emissions.

Without FOLU, the main GHG emitted is CH4, as a result of the large contribution of the agriculture sector, followed by CO2, N2O and HFC.

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Contribution of each gas to national total emissions without FOLU (%)

Gas 1994 2000 2005 2010 2015 2016

CO2 17.47% 16.89% 16.61% 21.77% 29.98% 33.85% CH4 69.57% 70.80% 71.77% 67.37% 60.00% 56.88% N2O 12.95% 12.30% 11.58% 10.43% 8.96% 8.14% HFC 0.00% 0.00% 0.03% 0.43% 1.05% 1.13%

As mentioned above, the GHG inventory of the Kingdom of Cambodia includes estimates of greenhouse gases as CO2, CH4, N2O and HFC. Besides, other gases, known as precursors, have been estimated for the energy sector.

The following table shows the emissions estimated by gas and sector for year 2016.

Emissions by category and gas, year 2016

Inventory Sector CO2 CH4 N2O HFC* NOX CO NMVOC SOx

(Gg)

Energy 8845.29 23.04 0.61 NA 43.43 160.46 45.03 32.61IPPU 1449.46 NA NA 371.68 NE NE NE NE Waste 814.55 79.7 0.82 NA NE NE NE NE Agriculture (3A + 3C)

17.42 645 7.56 NA NE NE NE

Forest and Other Land Use (FOLU) (3B)

131011.24 NA NA NA NA NA NA NA

Total (without FOLU)

11127.73 747.87 8.98 371.68 43.43 160.46 45.03 32.61

Total (With FOLU) 142137.97 747.87 8.98 371.68 43.43 160.46 45.03 32.61 Note – HFC data is provided in mass of CO2-eq

The evolution of all gases estimated in the inventory is shown in the following table:

Emissions (with FOLU) by gas (Gg)

Inventory Sector 1994 2000 2005 2010 2015 2016

CO2 29753.96 30102.41 30544.23 136796.33 140125.72 142137.97CH4 435.61 516.92 609.19 715.96 729.63 747.87 N2O 6.80 7.54 8.25 9.30 9.14 8.98

HFC* - - 6.32 114.10 320.24 371.68 NOx 14.46 16.70 17.27 31.80 39.20 43.43 CO 68.62 69.85 66.27 138.80 137.61 160.46

NMVOC 23.44 25.22 23.11 54.04 43.99 45.03 SO2 2.51 3.15 4.08 14.71 27.40 32.61

Note – Emissions of HFC are provided in terms of Gg CO2-eq .

1

Preface

This document contains product 04 of the project “Development of the national greenhouse gas inventory (GHG-I) and the GHG-I and the Mitigation Actions chapters of Cambodia’s first Biennial Update Report”, funded by UNDP within the project Forest Carbon Partnership Facility II.

The Centre Interprofessional Technique d´Etudes de la Pollution Atmospherique (Citepa) subcontracting Gauss International Consulting S.L., was awarded the contract for developing the project, which started on the 01/08/2018 and will end on the 30/04/2018, as specified in the contract signed between the UNDP and CITEPA. For the development of the project, Citepa and Gauss (hereinafter international team) work in close collaboration with the National GHG-I Team and the Cambodian REDD+ taskforce and in consultation with relevant national stakeholders.

This document presents the revised draft of the edition 2019 of the GHG emissions inventory of Cambodia.

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1. Introduction

This document presents the 2019 edition of the National Greenhouse Gas (GHG) emissions inventory of the Kingdom of Cambodia that covers the GHG emissions of years 1994-2016. This inventory has been estimated following the 2006 IPCC Guidelines, and has been compiled with the involvement of a national inventory compilation team and the focal points of the main line ministries of the country.

Gases

This inventory addresses the estimation of the main direct greenhouse gases: Carbon Dioxide (CO2), Methane (CH4), Nitrous oxide (N2O) and Hydrofluorocarbons (HFC). Due to the lack of information on their occurrence, the emissions of Perfluorocarbons (PFC), Sulfur hexafluoride (SF6) and Nitrogen trifluoride (NF3) have not been estimated.

The gases which are considered ozone precursors: carbon monoxide (CO), oxides of nitrogen (NOx), non-methane volatile organic compounds (NMVOCs), and Sulphur dioxide (SO2), which are also reported in national GHG emissions inventories, have not been estimated in an exhaustive manner in all the sectors (the reasons are explained in the corresponding sections of this national inventory report).

Sectors and categories

Greenhouse gas emission and removal estimates are divided into the main sectors of the 2006 IPCC Guidelines, which are groupings of related processes, sources and sinks:

Energy Industrial Processes and Product Use (IPPU) Agriculture, Forestry and Other Land Use (AFOLU) Waste

Each sector comprises individual categories (e.g., transport) and sub-categories (e.g., cars). A national total is calculated by summing up emissions and removals for each gas.

An exception is emissions from fuel use in ships and aircraft engaged in international transport which is not included in national totals but is reported separately.

Reporting of emission estimates is generally organised according to the sector actually generating emissions or removals. There are some exceptions to this practice, such as CO2 emissions from biomass combustion for energy, which are reported in AFOLU Sector as part of net changes in carbon stocks.

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Methodology

Overall, the 2006 edition of the IPCC Guidelines has been followed for estimating the GHG emissions and removals of the inventory. For estimating the emissions of precursors, the Guidelines of EMEP/EEA 20161 have been used, as proposed by IPCC.

The details of the methodology used for each category are specified in the corresponding methodological sections of the report.

Both the 2006 IPCC and the EMEP/EEA 2016 Guidelines provide methodologies of different complexity (tiers 1 to 3) which can be used in different circumstances and are generally based in linear models.

The basic equation for estimating the emission of one category is the following:

{1} 𝐸𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑠 , , 𝐴𝐷 , ∙ 𝐸𝐹 , , Where 𝐸𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑠 , , 𝑒𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑠 𝑜𝑓 𝑐𝑎𝑡𝑒𝑔𝑜𝑟𝑦 𝑐, 𝑔𝑎𝑠 𝑔 𝑎𝑛𝑑 𝑦𝑒𝑎𝑟 𝑡 𝐴𝐷 , 𝑎𝑐𝑡𝑖𝑣𝑖𝑡𝑦 𝑑𝑎𝑡𝑎 𝑜𝑓 𝑐𝑎𝑡𝑒𝑔𝑜𝑟𝑦 𝑐, 𝑦𝑒𝑎𝑟 𝑡 𝐸𝐹 , , 𝐸𝑚𝑖𝑠𝑠𝑖𝑜𝑛 𝑓𝑎𝑐𝑡𝑜𝑟 𝑜𝑓 𝑒𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑠 𝑜𝑓 𝑐𝑎𝑡𝑒𝑔𝑜𝑟𝑦 𝑐, 𝑔𝑎𝑠 𝑔 𝑎𝑛𝑑 𝑦𝑒𝑎𝑟 𝑡

The estimates of emissions and removals– in its simplest form- correspond to a direct relation between an emission factor (emission rate by unit of activity) and the activity data which represents the corresponding level of activity.

The activity data describes the annual magnitude of one activity (for instance, cement production, fuel consumption, etc, at national level, for one category and one year).

The emission factor is the amount of gas emitted by unit of activity (for instance, Gg of CH4 by tonne of fuel consumed). Default emission factors are provided by the 2006 IPCC Guidelines for the direct GHGs and by EMEP/EEA 2016 Guidelines for the precursors.

In many cases, the activity data available do not correspond to the emission factor available or used. In these cases, the data need to be converted using conversion factors. In such cases, the equation is the following:

{2} 𝐸𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑠 , , 𝐴𝐷 , ∙ 𝐸𝐹 , , ∙ 𝐶𝑜𝑛𝑣𝑒𝑟𝑠𝑖ó𝑛 𝑓𝑎𝑐𝑡𝑜𝑟

All the equations require of a statistical value which needs to be obtained from the entities which collect regularly the data.

1 https://www.eea.europa.eu/publications/emep-eea-guidebook-2016

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There are several IPCC methods that can be used for estimating emissions and removals. The choice of one method depends on the availability of data, the current circumstances of the country and the human and financial resources to elaborate the inventory.

In the IPCC terminology, the simplest method is “tier 1”, while “tier 2” and “tier 3” are more advanced methods.

Tier 1 methods use default emission factors provided by 2006 IPCC Guidelines which require basic national activity data.

Tier 2 methods use more detailed methodologies using national specific emission factors, technology specific emission factors and/or regional emission factors and require data which certain level of disaggregation (higher breakdown than tier 1).

Tier 3 methods use models, data from surveys or direct measurements.

It is important to use higher tier methods for those categories which the country considers more important. For this reason, the first phase in the inventory development was to analyse the key categories using the results of inventories previously reported in the first and second national communication. In practice, tier 1 methodologies are used for categories with low impact in the inventory, tier 2 methodologies are used for categories with significant impact on the inventory, as much as the national circumstances allow it, and tier 3 methodologies are used in categories with very high impact on the inventory (improvement plans should focus in obtaining progressively more detailed and national specific data for enabling the country to use higher tiers and thus produce much more accurate and precise emissions and removals estimates).

Nevertheless, due to the lack of availability of data and the absence of national specific emission factors, the emissions and removals estimates have been performed using a tier 1 methodology for most categories, gases and years.

Specifically, the categories, gases and years for which a tier 2 methodology is applied are the following:

‐ Cement production CO2 emissions for the years 2007-2015, as plant specific data on clinker production is available.

‐ Land CO2 emissions for the years 1994-2016, as the calculations for the lands are based on a comprehensive monitoring of the land use and a country specific estimate for each type of land.

Data Sources

The activity data used for developing the inventory is mainly the information which is available at national level and was obtained by the inventory coordinator for the different categories of each sector from the national compilation team. Despite the efforts made, the scarcity of data has been the main challenge for developing estimates in all sectors and emission sources and removals.

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In the cases in which the information available at national level was not enough for developing estimates in line with the IPCC guidelines, international sources of data have been used and assumptions made using expert judgment.

All sectors include an improvement plan for improving the quality of the inventory in the future. For all sectors the improvement plan is mainly focused on improving the information available from national sources.

Regarding the emission factors and other coefficients, the 2006 IPCC Guidelines were used as a primary source of information. Nevertheless, the Guidelines have been complemented with other sources when necessary. All the cases in which the 2006 IPCC Guidelines have not been used are specified in the report.

Global Warming Potentials

The Global Warming Potential (GWP) was developed to allow comparisons of the global warming impacts of different gases. The larger the GWP, the more that a given gas warms the Earth compared to CO2 over a time period. The time period usually used for GWPs is 100 years. GWPs provide a common unit of measure, which allows to add up emissions estimates of different gases and thus to compile a national GHG inventory.

In the Conference of the Parties (COP) decisions, Parties may use GWPs to reflect their inventories and projections in CO2 eq terms. In such cases, the 100-year time-horizon values provided by the IPCC in its Special Reports should be used.

In 2002 the COP by its decision 17/CP.8 decided that non-Annex I Parties wishing to report on aggregated GHG emissions and removals expressed in CO2 eq should use the “1995 IPCC GWP Values” based on the effects of GHGs over a 100-year time horizon. At the same time, by its decision 18/CP.8, it decided that Annex I Parties should report aggregate emissions and removals of GHGs, expressed in CO2 eq using the same “1995 IPCC GWP Values” based on the effects of GHGs over a 100-year time horizon.

In 2013, under the framework of the UNFCCC reporting guidelines on annual inventories for Annex I Parties, the COP, by decision 24/CP.19, decided that, from 2015, the GWPs used to calculate the CO2 equivalence of emissions and removals of GHGs shall be, also those listed in the column entitled “Global warming potential for given time horizon” in table 2.14 of the errata to the contribution of Working Group I to the Fourth Assessment Report of the IPCC, based on the effects of GHGs over a 100-year time horizon.

Under the Convention, the Subsidiary Body for Scientific and Technological Advice (SBSTA) 44 (2016) noted that the COP requested the Ad Hoc Working Group on the Paris Agreement (APA) to elaborate guidance for accounting for Parties’ nationally determined contributions which ensures that accounting is in accordance with common metrics assessed by the IPCC (1/CP.21, paragraph 31). Therefore, the SBSTA agreed to defer the consideration of common metrics to SBSTA 46 (May 2017) so as to be able to take into account deliberations under the APA. During SBSTA 47 (November 2017) Parties recognized that further consideration of common metrics by the APA was necessary and agreed to resume consideration of common metrics at SBSTA 50 (June 2019), so as to be able to take into account the deliberations under

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the APA on this matter. The APA concluded its deliberations at CMA 1 (December 2018), and Parties agreed that Parties account for anthropogenic emissions and removals in accordance with common metrics assessed by the IPCC and in accordance with decision 18/CMA.1 (decision 4/CMA.1, annex II, paragraph 1(a)). Pursuant the modalities, procedures and guidelines (MPGs) for the transparency framework for action and support adopted by decision 18/CMP.1, Parties agreed to use the 100-year time-horizon GWP values from the Fifth Assessment Report of the IPCC, or 100-year time-horizon GWP values from a subsequent IPCC assessment report as agreed upon by the CMA, to report aggregate emissions and removals of GHGs, expressed in CO2 eq. (decision 18/CMA.1, annex, paragraph 37).

In order to prepare an inventory aligned with the second commitment period of the Kyoto protocol of Annex I Parties using 2006 IPCC Guidelines, the GWP used for the 2019 Edition of the Cambodian GHG inventory are the 100-year time-horizon GWP values from the errata table of the Fourth Assessment Report of the IPCC.

Notation keys

The use of Notation keys is a good practice for fulfilling the reporting tables contained in inventory reports. Notation keys are needed when the estimates of emissions and sinks are not made or if there is any clarification needed for a specific source when a numeric value is not provided. Notation keys are used to account for completeness and transparency in reporting.

Table 1 – Notation keys

Notation Key Definition Explanation

NE Not estimated Emissions and/or removals occur but have not been estimated or reported.

IE Included elsewhere

Emissions and/or removals for this activity or category are estimated and included in the inventory but not presented separately for this category. The category where these emissions and removals are included should be indicated (for example in the documentation box in the correspondent table).

C Confidential information

Emissions and/or removals are aggregated and included elsewhere in the inventory because reporting at a disaggregated level could lead to the disclosure of confidential information.

NA Not applicable The activity or category exists but emissions and removals are considered never to occur.

NO Not occurring An activity or process does not exist within a country. Source: Chapter 8; volume 1, 2006 IPCC Guidelines

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2. National system

In the context of national GHG emission inventories, a national system is the way in which a country prepares its inventory. The design and establishment of an inventory national system is a requirement for developed countries (Annex I Parties) under the Convention. The guidelines for national systems for Annex I parties2 provides the following definition:

“A national system includes all institutional, legal and procedural arrangements made within a Party included in Annex I for estimating anthropogenic emissions by sources and removals by sinks of all greenhouse gases not controlled by the Montreal Protocol, and for reporting and archiving inventory information”.

Developing countries (non-Annex I Parties) under the Convention are not required to establish GHG emissions inventory national systems. However, the guidelines for the preparation of national communications and biennial update reports for non-annex I parties include similar information provisions, as follows:

Decision 17/CP.8, annex, paragraph 13: “Non-Annex I Parties are encouraged to describe procedures and arrangements undertaken to collect and archive data for the preparation of national GHG inventories, as well as efforts to make this a continuous process, including information on the role of the institutions involved”.

Aiming at fulfilling the information provision for the Biennial Update Report (BUR) and National Communication (NC), this section includes a description of the institutional arrangements in place in Cambodia for the preparation of the GHG emissions inventory, as well as a description of the inventory preparation and management procedures established that have enabled the preparation of the inventory.

The development of GHG emission inventory is framed under the preparation of the First BUR of the country. Hence, references are made to the arrangements in place for the development of the first BUR of Cambodia.

2.1. Institutional arrangements for compiling GHG inventory

In the fifth mandate of the Royal Government of Cambodia, the Ministry of Environment (MoE) was officially reformed aiming at strengthening the function of natural resource management and ensuring environmental quality management in the context of sustainable development. Along the reform of the MoE, the National Council for Sustainable Development (NCSD) was established by the sub-decree No. 59 dated 18 May 2015 with the objective of improving the inter-ministerial coordination for addressing the sustainable development challenge. Thus, the NCSD is a high-level inter-ministerial mechanism created to prepare, coordinate, and monitor the implementation of policies, strategies, plans and programmes related to sustainable development. The NCSD is chaired by minister of environment and is supported by the General Secretariat for Sustainable Development (GSSD). As part of the GSDD, The Department of Climate Change (DCC) is responsible for formulation of draft climate change plans and policies and serves as secretariat to the Cambodian Government’s focal points for UNFCCC, the

2 Decision 19/CMP.1

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Intergovernmental Panel on Climate Change (IPCC), the Kyoto Protocol and the Clean Development Mechanism (CDM) and other mechanisms. DCC also coordinates inter-ministerial Technical Working Groups (TWGs) by sectors and themes (GHG inventory, mitigation, vulnerability and adaptation, and UNFCCC implementation). DCC also supports the climate change activities of the NCSD and acts as the coordinating agency for UNFCCC reporting.

It is also worth highlighting that the Cambodia REDD+ programme was transferred from Ministry of Agriculture, Forestry and Fisheries to the MoE and is now under direct management and implementation of the General Directorate of Administration for Nature Conservation and Protection (GDANCP) within the MoE. The Cambodia REDD+ programme and its secretariat have key responsibilities in formulating forest policies, strategic and action plans aligning with Cancun decision and Warsaw framework on REDD+.

Figure 1 – Simplified organization chart of the Ministry of Environment

Note – G.D. General Directorate

The NCSD through the GSSD and the DCC have the overall responsibility for the inventory preparation. Nevertheless, Cambodia does not count yet with a sustainable inventory compilation unit or exhaustive institutional arrangements for inventory planning, preparation and management.

For the development of the 2019 edition of the GHG inventory, the GSSD signed a letter of agreement (LoA) with the GDANCP to assist the DCC in the preparation of national greenhouse gas inventory and the inventory chapter of the BUR. Thought this letter, the GDANCP has acted as inventory coordinator for the preparation of the 2019 edition of the inventory. A national and an international compilation team were temporally contracted for the preparation of the inventory.

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Figure 2 – Structural arrangements for the GHG inventory compilation 2016

(Note: this diagram is designed for this third GHG-I only)

For the development of the 2019 edition of the GHG emission inventory, which covers the years 1994-2016, the detailed roles and responsibilities for the inventory development are the following:

Table 2 – Roles and responsibilities for the development of the GHG-I

Role Responsibility Climate Change lead agency

Validation of results, supervision and strategic oversight

Inventory coordinator Coordinate and oversee the work of international and national consultants.

UNDP coordinator Oversee the work of the international compilers and supports the coordination with the national inventory coordinator.

International inventory compilers

Estimate the GHG emission inventory, perform quality control processes, write the inventory report and provide capacity building to national compilers.

National inventory Compilers

Gathering activity data, supporting the compilation of GHG emissions estimates and perform quality checks in line with the QA/QC plan.

International QA experts Carry out the quality assurance of the inventory, in line with the QA/QC plan.

Data providers Provide the information available as needed for the development of the national inventory.

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2.2. Inventory planning, inventory preparation and inventory management

The 2006 IPCC Guidelines for the development of national GHG emission inventories recommend a set of steps to follow for the inventory compilation. These steps are the inventory development cycle, which encompass all the tasks needed to produce a national GHG emission inventory in line with good practice.

The following figure illustrates the inventory development cycle for Cambodia, based on the steps proposed by 2006 IPCC Guidelines.

Figure 3- Inventory development cycle in Cambodia

Source: Adapted to Cambodia based on 2006 IPCC Guidelines, Volume 1, Chapter 1.

A description of all tasks developed within each of the steps of the inventory cycle for the inventory edition of 2019 is provided below.

Identification of key categories

Key category analysis is the IPCC’s method for deciding which emissions or removals categories to prioritize in GHG inventory estimation (categories that should use progressively higher tier methods to increase accuracy and decrease uncertainty of the estimates).

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A category is key if, when categories are ordered by magnitude, it is one of the categories contributing to 95% of total national emissions or removals, or to 95% of the trend in national emissions or removals.

Key category analysis may need to be iterative; the initial ordering may need to be undertaken using Tier 1 methods, since it is not yet known which categories are keys.

The inventories reported in the First and the Second National Communications were analysed for a preliminary identification of key categories.

The first National Communication was submitted in 2002 and included the emissions of the inventory year of 1994. The second National Communication was submitted in 2016 and included the emissions of the inventory year 2000.

Based on the most updated NC, total national GHG emissions of the country for year 2000 are -456.81kt CO2-eq. Energy sector emissions are 2,767.30 kt CO2-eq, Agriculture 21,112.16 kt CO2-eq, Land Use, Land Use Change and Forestry (LULUCF) -24,565.50 kt CO2-eq and waste 229.24 kt CO2-eq. These figures illustrate that the AFOLU sector (Agriculture plus LULUCF, as of 2006 IPCC Guidelines) is dominant for explaining national total GHG emissions of the country. The IPPU sector was not reported in the Second National Communication, but it was in the First National Communication.

For their contribution to the level of emissions, the categories of transport, energy industries and forestry and other land use were identified as key categories.

For its possible contribution to the trend (i.e. the change of emissions from the first to the second national communication), the categories of solid waste disposal, rice cultivation, cement production and manufacturing industries were identified as key categories.

Data Collection

The development of the GHG emission inventory was based on the information available at national level that could be used for estimating the emissions of the different emission sources of the Common Reporting Format (CRF) and the 2006 IPCC Guidelines.

The 2019 inventory edition started from an initial planning phase for developing a detailed work plan for the development of the inventory, considering the prospective information requirements for implementing tier 1 methodologies. Accordingly, data questionnaires by sector (for the Energy, Industrial Processes and Product Use, Waste and Agriculture, Forestry and Other Land Use sectors) were generated and presented to possible data providers and stakeholders.

These questionnaires were used for gathering information from official sources.

The data gathered from official sources was complemented by international sources or assumptions. All data sources and assumptions are specified in the calculation files and in this national inventory report to ensure the transparency of the estimates.

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Finally, the cases in which there was no data from national sources, proposals were performed in the improvement plans at sectoral level.

The following table shows all the data sources by emission source as used for the 2019 GHG emission inventory edition.

Table 3 – Main sources of information used for the development of the inventory

Sector Description of the data Data Provider

Energy

Energy statistics for the period 2010-2015

Economic Research Institute for ASEAN and East Asia (ERIA)

Energy balances 2010-2016 Ministry of Mines and Energy

Energy statistics for the period 1995-2012 Association of South East Nations (ASEAN)

IPPU

Production data for years 2014-2017 Ministry of Industry and Handicrafts

Cement Production capacity and plant year of installation

Different sources online such as industrial papers and news on starting industrial operations

Production data from one cement production plant One producer company

Fuel (Lubricant) consumption data Cambodia Energy Statistics – ERIA and the Ministry of Mines and Energy

Cambodia HFC inventory for the period 2012-2015

The National Ozone Unit of the Ministry of Environment

Population and GDP data sources from period 1950-2016

CDB data, NCDD, Socio-economic survey and World bank data

AFOLU

Crops data Animal populations, crop areas and productions from Ministry of Agriculture, Forestry and Fisheries (MAFF). Livestock

Land activity data for period 2006-2010 and 2010-2014

Cartography matrix from the work developed under the preparation of the Forest Reference Level

Biomass burning from rice cultivation

Vibol, S., & Towprayoon, S. (2010). Estimation of methane and nitrous oxide emissions from rice field with rice straw management in Cambodia. Environmental monitoring and assessment, 161(1-4), 301-313.

Rice cultivation data period before 2004

MAFF publications for both wet and dry seasons

Rice cultivation data period since 2005 FAOSTAT

Waste

Population data

Data from the National Committee for sub-national Democratic Development complemented with the world bank database

GDP data GDP from the MOP complemented with the world bank database

Waste composition Study “State of Waste Management in Phnom Penh, Cambodia”, UNEP 2018. Available at

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Sector Description of the data Data Provider

Waste generation Ministry of Environment

Amount of dung used for producing biogas

Hyman, J., & Bailis, R. (2018). Assessment of the Cambodian National Biodigester Programme. Energy for Sustainable Development, 46, 11-22. Energy balance of the Ministry of Mines and Energy

Protein consumption FAO data

Percentage of people open burning waste

Yut S. and Seng B., 2018. KAP on waste management (data of 2012)

Inventory compilation

The inventory compilation was performed using Excel worksheets, which include the raw information used for the estimation of the GHG emissions of each category, the coefficients used, the results obtained, and the QA/QC procedures followed. These Excel files were developed to be self-explanatory and can be used as a starting point for developing future national inventories. These are at the same time working files and an inventory excel database.

The 2006 IPCC Software was used only as a complimentary approach, just for QA purposes. The reason for doing that is the limited flexibility of the software for developing national tier2/tier3 approaches, the limitations for being used as a database (for instance, for including raw data as provided by data providers) and also for its constraints regarding national specific calculations to be done on the parameters used such as activity data, emission factors or other coefficients.

Several worksheets were developed by sector. In general, the worksheets follow the structure proposed by IPCC in its calculation worksheets, available at https://www.ipcc-nggip.iges.or.jp/public/2006gl/vol2.html.

The overall structure of the worksheets is the following:

Sheet “Introduction”: this sheet includes a description of the objective of the file, the categories or emission sources considered in the file, the description of the activity data used and the list of sheets in the file.

Sheet “Summary table”: This sheet includes the sectoral report table for the sector. Sheet “Results”: this sheet provides the results for all the time series for the different

gases estimated in both CO2-eq and mass.

The calculation sheets include links to the raw data used in the calculations, so it can be easily tracked. To the extent possible, a system of colors has been used: sheets coloured in light red and light yellow are raw data as provided by different data providers. Sheets coloured in green contain the calculations, results and key methodological variables used for the development of the inventory.

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QA/QC Plan

A QA/QC plan has been developed to describe the Quality Assurance and Quality Control procedures in place to ensure the datasets meet the quality requirements and to explain the data processing steps required for producing the datasets.

The QA/QC plan covers the following processes:

GHG inventory management, comprising all activities that are necessary for the planning and preparation of the inventory in order to ensure the accomplishment of the above-mentioned objectives and principles.

Quality control that is directly related to the estimation of emissions. The process includes activities related to (a) data inquiry, collection and documentation, (b) methodological choice in accordance with the 2006 IPCC Guidelines, (c) quality control checks for data from secondary sources and (d) record keeping.

Archiving inventory information, comprising activities related to centralised archiving of inventory information and the compilation of the national inventory report.

Quality assurance, comprising activities related to the different levels of review processes including the review of input data from experts, if necessary, and comments from the validation workshop with all relevant national stakeholders.

Estimation of uncertainties, defining procedures for estimating and documenting uncertainty estimates per source / sink category and for the whole inventory.

Inventory improvement that is related to the preparation and the justification of any recalculations or the generation of new estimates.

The objectives of the QA/QC Plan are the following:

1. Compliance with the 2006 IPCC guidelines and the UNFCCC reporting guidelines while estimating and reporting emissions/removals.

2. Continuous improvement of GHG emissions/removals estimates. 3. Timely submission of necessary information in compliance with relevant requirements

defined in international conventions, protocols and agreements.

The five principles for this QA/QC plan are shown in the table below. These principles are interrelated and apply at various levels in the data compilation and reporting processes.

Table 4 – Guiding principles of the QA/QC

Principles Procedures in place to quality check if the principle is implemented

Transparency means clear documentation and reporting at a level of disaggregation that sufficiently allows individuals other than the compiler of the inventory to understand how the inventory was compiled. The transparency of emission reporting is fundamental to the effective use, review and continuous improvement of the inventory.

Check if documentation within the spreadsheets shows data inputs, calculations and outputs. Check if the chapters and sections within the NIR provide the activity data and emission factors with the sources used, explain the methods used and summarise the data set.

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Principles Procedures in place to quality check if the principle is implemented

Consistency means that estimates for any different inventory years, gases and source categories are made in such a way that differences in the results between years and source categories reflect real differences in emissions. Annual emissions, as far as possible, should be calculated using the same method and data sources for all years, and resultant trends should reflect real fluctuations in emissions and not the changes resulting from methodological differences.

Check if the same methods and the same data sources are used for the whole time series.

Comparability means that the national inventory is reported in such a way that allows it to be compared with national inventories of other Parties. This can be achieved by using accepted methodologies and by using the reporting templates such as those provided in the 2006 IPCC Guidelines.

Check if the same IPCC guidelines for the methodologies and reporting templates have been used for the whole inventory and for the same group of gases (GHG or precursors).

Completeness means that estimates are reported for all gases, all relevant source categories and all years and for the entire territorial areas of Parties covered by the reporting requirements set forth in the provisions of the Convention and its protocols.

Specific checks have to be made to ensure that estimates are provided for all gases, all source categories existing in the country and the whole national territory. Check if emissions from international transport are not part of the totals but provided as memo items.

Accuracy means that emissions are neither overestimated nor underestimated, as far as can be judged and with uncertainties reduced as far as practicable. This implies that Parties will endeavour to remove bias from the inventory estimates and minimize uncertainty.

Check if uncertainty analysis is undertaken and improvement plans proposed. Check if the most appropriate and up to date data sources and methods are used.

The accomplishment of the above-mentioned objectives can only be ensured by the implementation, from all the members of the Inventory Team and the external peer reviewers, of the QA/QC procedures included in the plan for:

data collection and processing, applying methods consistent with 2006 IPCC Guidelines for calculating /

recalculating emissions or removals, making quantitative estimates of inventory uncertainty, archiving information and record keeping and compiling national inventory reports.

Section Results of the QA/QC presents the results of the quality control and quality assurance carried out for the 2019 edition of the Cambodian GHG inventory.

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Documentation and archiving

For the development of the 2019 edition of the inventory, an electronic platform was dedicated specifically for archiving the information used, the files generated and all the reports and supporting information used for the preparation of the inventory. This platform was managed and oversee by the coordinator of the GHG inventory.

The main objectives of the archiving system are preventing information loss, and facilitate the update of future inventories. The information archives will be also used for providing information in the technical analysis of the BUR.

3. GHG emissions inventory – edition 2019

The following sections provide information about the results obtained, data used, methodology followed by category of emissions and removals. This information corresponds to the 2019 edition of the national GHG inventory of the Kingdom of Cambodia. The nomenclature followed is the one used by the 2006 IPCC Guidelines, as follows:

Table 5 – Nomenclature used

Inventory sector Code Energy 1 Industrial Process and Products Use (IPPU) 2 Agriculture, Forest and Other Land Use (AFOLU) 3 Waste 4

Each sector comprises individual categories (in capital letter), sub-categories (number) and sources/sinks (lowercase letter). A complete list of codes, categories and emissions, are provided in the reporting tables in each section of the report.

Overall, the 2006 IPCC Guidelines have been followed for estimating the GHG emissions and removals of the inventory. For estimating the emissions of precursors, the EMEP/EEA 2016 Guidelines have been used, as proposed by IPCC.

The global warming potentials used for the calculation of the total GHG emissions are those of the AR4, as follows:

Table 6 - Global Warming Potentials (GWP) used

Global Warming Potential Gas GWP

CO2 1CH4 25N2O 298HFC134a 1 430HFC125 3 500HFC143a 4 470HFC32 675HFC-227ea 3 220

Source: IPCC Fourth Assessment Report (AR4)

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3.1. Emissions trends (1994-2016) This report presents the results, methodologies and information used for estimating the GHG emissions of the Kingdom of Cambodia for the years 1994-2016 for the sectors of Energy, Industrial process and Products Use (IPPU), Agriculture, Forestry and Other Land Use (AFOLU) and Waste.

The emissions of direct Greenhouse gases are pondered using the global warming potentials extracted from the IPCC Fourth Assessment Report (AR4), in terms of gigagrams (Gg) or kilotonnes (kt) of CO2-eq for the CO2, CH4, N2O and HFC. PFC, SF6 and NF3 have not been estimated due to the lack of information available.

The emissions of greenhouse gases estimated for the total of the inventory including Forestry and Other Land Use (FOLU) are 163 882 Gg of CO2-eq for year 2016, which is a 284 per cent higher than emissions in 1994. The main driver for this increase in GHG emissions is the deforestation reflected in the emissions of the FOLU sector. Without FOLU, the GHG emissions are 32 871 Gg of CO2-eq for year 2016, which is a 110 per cent higher than the emissions in 1994.

The next table provides an overview of the emissions of each inventory sector for the years 1994, 2000, 2005, 2010, 2015 and 2016.

Table 7- Trend of emissions (GHG, Gg CO2-eq)

Inventory Sector 1994 2000 2005 2010 2015 2016

Energy 2 690.95 3102.73 3454.41 5306.37 8356.31 9601.61 IPPU 3.81 6.04 12.73 492.84 1001.38 1821.15 Waste 1756.18 2111.61 2415.89 2633.62 2974.53 3050.67 Agriculture (3A + 3C)

11202.58 13032.31 15336.38 18136.08 18068.35 18397.67

Forest and Other Land Use (FOLU) (3B)

27018.62 27018.62 27018.62 131011.24 131011.24 131011.24

Total (without FOLU) 15653.52 18252.70 21219.42 26568.91 30400.57 32871.10

Total (with FOLU) 42672.14 45271.32 48238.04 157580.15 161411.82 163882.35

As illustrated in the following figure, the emissions of all sectors present an increasing trend from 1994 to 2016.

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Figure 4 - GHG emissions; Years 1994-2016 (Gg of CO2-eq)

The major contributor to the GHG emissions during the entire period is the Forest and Other Land Use sector (FOLU), which is driven by the change in carbon stocks due to deforestation and other changes in the land use.

The second largest emitter sector in the country is the Agriculture sector. Cambodia has an economy which is strongly marked by the contribution of agriculture to total GDP, and that is also reflected in the emission pattern. The main driver for the GHG emissions increase in the agriculture sector is the development of the rise cultivations, whose activity level and emissions increased by a rate of ~2.5 in the period 1994-2016.

In the time span covered by the inventory, Cambodian GDP has experienced a significant expansion, along its population. This is reflected in the increasing trend of the emissions of the third and fourth largest emitter sectors in the country, the Energy and Waste sectors, respectively. The energy demand has experienced a significant increase, transport sector is expanding, and the population is migrating to cities; all these factors combined led to increasing fuel consumption and higher GHG emissions in the energy sector. The increased population and the changes in waste management and sanitation are the main drivers for the emissions of the waste sector.

Last but not least, the small size of the carbon intensive-industrial sector in the country makes the IPPU the fifth contributor the national total GHG emissions. Nevertheless, IPPU sector emissions experienced a growing expansion in the last period of the series, due to the raising contribution of cement production and the consumption of fluorinated gases.

Emissions (including FOLU) per cápita have increased from 4.00 to 10.44 tonnes CO2-eq/ inhabitant/year. This increase is mainly due to the high deforestation produced in the country. Conversely, GHG emissions (including FOLU) per unit of GDP have been reduced from a 15.41 to 8.26 tonnes Co2-eq/thousand USD/year. This reduction is due to the fact that the expansion of GDP is significantly higher than the increase of GHG emissions.

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

180,000

Energy IPPU Waste Agriculture FOLU

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The following figure shows the percentage of emissions of each inventory sector for years 1994 and 2016.

Figure 5 – Percentage of emissions by sector (as of % of CO2-eq)

The previous figure shows the decreasing contribution to total national emissions in 2016 compared to 1994 in the sectors of energy, waste and agriculture, and the increase in the contribution of FOLU and IPPU.

In terms of the contribution of each GHG to national total emissions, CO2 is the main gas emitted, driven by the large contribution of the FOLU sector to national total emissions, followed by CH4, N2O and HFC.

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Table 8 - Contribution of each gas to national total emissions with FOLU (%)

Gas 1994 2000 2005 2010 2015 2016 CO2 69.73% 66.49% 63.32% 86.81% 86.81% 86.73% CH4 25.52% 28.55% 31.57% 11.36% 11.30% 11.41% N2O 4.75% 4.96% 5.09% 1.76% 1.69% 1.63% HFC 0.00% 0.00% 0.01% 0.07% 0.20% 0.23%

Note – This contribution is calculated converting first the emissions of each gas to CO2‐eq using global warming 

potentials 

The following figure provides an overview of the contribution of each sector to national total GHG emissions without considering the FOLU sector.

Figure 6 – GHG emissions without FOLU; Years 1994-2016 (Gg of CO2-eq)

The GHG emissions without the FOLU sector are dominated by the contribution of the agriculture sector and the increasing contributions of the energy and waste sectors. In year 2016, the split of emissions without FOLU by sector is the following: Agriculture 56.0%, Energy 29.2%, Waste 9.3% and IPPU 5.5%.

Without FOLU, the main GHG emitted is CH4, as a result of the large contribution of the agriculture sector, followed by CO2, N2O and HFC.

Table 9 - Contribution of each gas to national total emissions without FOLU (%)

Gas 1994 2000 2005 2010 2015 2016 CO2 17.47% 16.89% 16.61% 21.77% 29.98% 33.85%

CH4 69.57% 70.80% 71.77% 67.37% 60.00% 56.88%

N2O 12.95% 12.30% 11.58% 10.43% 8.96% 8.14%

HFC 0.00% 0.00% 0.03% 0.43% 1.05% 1.13%Note – This contribution is calculated converting first the emissions of each gas to CO2‐eq using global warming 

potentials 

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

Energy IPPU Waste Agriculture

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As mentioned above, the GHG inventory of the Kingdom of Cambodia includes estimates of greenhouse gases as CO2, CH4, N2O and HFC. Besides, other gases, known as precursors, have been estimated for the energy sector.

The following table shows the emissions estimated by gas and sector for year 2016. Complete reporting tables for all sectors are provided in section “Reporting tables”.

Table 10 - Emissions by category and gas, year 2016

Inventory Sector

CO2 CH4 N2O HFC* NOX CO NMVOC SOx (Gg)

Energy 8845.29 23.04 0.61 NA 43.43 160.46 45.03 32.61IPPU 1449.46 NA NA 371.68 NE NE NE NEWaste 814.55 79.7 0.82 NA NE NE NE NEAgriculture (3A + 3C) 17.42 645 7.56 NA NE NE NE

Forest and Other Land Use (FOLU) (3B)

131011.24 NA NA NA NA NA NA NA

Total (without FOLU) 11127.73 747.87 8.98 371.68 43.43 160.46 45.03 32.61

Total (With FOLU) 142137.97 747.87 8.98 371.68 43.43 160.46 45.03 32.61

Note – HFC data is provided in mass of CO2-eq

The evolution of all gases estimated in the inventory is shown in the following table:

Table 11 - Emissions (with FOLU) by gas (Gg)

Inventory Sector 1994 2000 2005 2010 2015 2016

CO2 29 753.96 30 102.41 30 544.23 136 796.33 140 125.72 142 137.97CH4 435.61 516.92 609.19 715.96 729.63 747.87N2O 6.80 7.54 8.25 9.30 9.14 8.98

HFC* NO NO 6.32 114.10 320.24 371.68NOx 14.46 16.70 17.27 31.80 39.20 43.43CO 68.62 69.85 66.27 138.80 137.61 160.46

NMVOC 23.44 25.22 23.11 54.04 43.99 45.03SO2 2.51 3.15 4.08 14.71 27.40 32.61

Note – Emissions of HFC are provided in terms of Gg CO2-eq . Detailed information by gas is provided under the IPPU sector.

Complete reporting tables are provided in section Reporting tables.

3.2. Energy sector 3.2.1. Characterization of the sector

The energy sector includes all the GHG emissions arising from combustion and fugitive releases of fuels. Based on the IPCC 2006 Guidelines, GHG emissions in the energy sector are split into three main sub-sectors: 1A Fuel Combustion Activities, 1B Fugitive emissions from fuels and 1C CO2 transport and storage. The description of the nature of the emissions included in each sub-sector is provided in the following table:

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Table 12 - Emissions included under the energy sector

Sector/sub-sector GHG emissions included

1. Energy sector All GHG emissions arising from combustion and fugitive releases of fuels. Emissions from the non-energy uses of fuels are generally not included here but reported under Industrial Processes and Product Use sector.

1A. Fuel combustion activities

Emissions from the intentional oxidation of materials within an apparatus that is designed to raise heat and provide it either as heat or as mechanical work to a process or for use away from the apparatus

1B. Fugitive emissions from fuels

Includes all intentional and unintentional emissions from the extraction, processing, storage and transport of fuel to the point of final use.

1C. CO2 transport and storage

Carbon dioxide (CO2) capture and storage (CCS) involves the capture of CO2, its transport to a storage location and its long-term isolation from the atmosphere.

Source: IPCC 2006 guidelines

The official energy balance of the Kingdom of Cambodia3 describes an energy sector significantly dependent on energy imports. From a total of 7 365 ktoes of primary energy supply for year 2016, only an amount of 4 336 ktoes were produced in the country, of which 4 107 ktoes corresponds to biomass. The remaining energy supply for year 2016 was fulfilled by hydrogeneration (225 ktoes) and other renewables (4 ktoes).

Regarding final energy consumption, the energy balance shows a total amount for year 2016 of 6 164 ktoes. The fuel which is more consumed in the country is biomass (3 530 ktoes), followed by oil products (2 111 ktoes), electricity (506 ktoes) and coal (17 ktoes).

In a more detailed analysis of the energy consumption of the country by sector using the latest data available on the sectoral split of fuel consumption (year 2015) 4, shows the transport sector as the main consumer of energy, with a 45% of total final energy consumption, followed by the residential/institutional/commercial sector, with a 39% of total final energy consumption, and Industry, with a 45%.

As a result of the energy profile of Cambodia, only the emissions of fuel combustion activities (1A Fuel Combustion activities) are estimated in the current inventory5.

Several categories are included within fuel combustion, as follows:

Table 13 - Emissions included under 1A Fuel Combustion activities

Category GHG emissions included

1A1. Energy industries Comprises emissions from fuels combusted by the fuel extraction or energy-producing industries. This includes emissions from main activity producers of electricity generation, combined heat and power generation, and heat plants; auto

3 Provided by the Ministry of Energy and Mines

4 This analysis is made using the data from the ERIA report for year 2015, which provides data with certain level of disaggregation regarding fuel consumption

5 As Cambodia is mainly an importer or fuels, fugitive emissions from fuels produce minor GHG emissions. CO2 transport and storage does not occur in the country.

23

Category GHG emissions included producers; and All combustion activities supporting the refining of petroleum products.

1A2. Manufacturing Industries and Construction

Emissions from combustion of fuels in industry. Non-energy consumption of fuels is not included here by in the IPPU sector.

1A3. Transport Emissions from the combustion and evaporation of fuel for all transport activity (excluding military transport). Emissions from fuel sold to any air or marine vessel engaged in international transport are excluded from national totals

1A4. Other Sectors Emissions from combustion activities in the commercial and institutional buildings, in the residential sector and emissions from fuel combustion in agriculture, forestry, fishing and fishing industries.

The following table provides a summary of the emissions for the energy sector in year 2016. Complete reporting tables are provided in section Reporting tables.

Table 14 - Summary of emissions – Energy sector –GHG emissions of year 2016

GREENHOUSE GAS SOURCE AND SINK CATEGORIES

CO2 CH4 N2O HFC SF6 NOX CO NMVO

C SO2

(Gg)

Total Energy 8 866.28 22.87 0.61 NA NA 43.43 160.46 45.03 32.61 A. Fuel combustion activities (sectoral approach)

8 866.28 22.87 0.61 NA NA 43.43 160.46 45.03 32.61

1. Energy industries 2 990.41 10.05 0.05 NA NA 9.23 3.47 0.29 25.142. Manufacturing industries

and construction 710.77 1.14 0.16 NA NA 6.95 23.32 11.39 3.12

3. Transport 4 993.03 1.21 0.24 NA NA 19.61 86.54 8.61 3.254. Other sectors 172.07 10.46 0.17 NA NA 7.64 47.14 24.73 1.095. Other (as specified in table

1.A(a) sheet 4) NO NO NO NO NO NO NO NO NO

B. Fugitive emissions from fuels

NO NO NO NO NO NO NO NO NO

Memo items: (1) International bunkers 236.49 0.00 0.01 NA NA 0.83 94.44 1.50 0.08

Aviation 236.49 0.00 0.01 NA NA 0.83 94.44 1.50 0.08 Navigation NE NE NE NE NE NE NE NE NE

CO2 emissions from biomass

13 694.77

CO2 captured NO

3.3.2. Data sources

There are three data sources for the energy sector:

Economic Research Institute for ASEAN and East Asia (ERIA) – ERIA statistics – complete energy statistics for the period 2010-2015, and partial data for 2007-2010.

Energy balance 2010-2016 of the Ministry of Mines and Energy Association of South East Nations (ASEAN) database: Energy statistics for the

period 1995-2012

ERIA statistics are considered by national stakeholders a more exhaustive and complete source of data. These statistics were produced as a result of surveys developed to fill the

24

existent data gaps; and was developed by a team of experts which combined international and national expertise. The dataset of ERIA was validated by national stakeholders. Nevertheless, the ERIA dataset was only complete for years 2010-2015, with year 2015 being only preliminary. For this reason and aiming at providing a complete and consistent time series for years 1995-2016, the three data sources have been combined for producing the activity data series of each emission category. Year 1995 is subrogated (1994) to provide time series up to the year presented in the first national communication.

The following figure shows the evolution of fuel consumption which has been used for estimating the emissions of the inventory. This time series has been estimated by the inventory team based on the data provided by the aforementioned sources of information.

Figure 7– Fuel consumption of Cambodia 1994-2016 – Data in ktoes

The previous figure shows that the fuel consumption of the country is driven by the consumption of biomass, the fuel with higher contribution to national total fuel consumption. Biomass consumption occurs in the residential sector, in the energy industries (production of electricity and charcoal) and industry. Biomass is followed by gas/diesel and motor gasoline, primarily used in the transport sector.

3.3.3. Energy emissions by category

Regarding methodologies, the most detailed data available in the country has been used to estimate through a sectoral approach the emissions of category 1A Fuel Combustion activities.

In the sectoral approach, the emissions are estimated using a bottom-up procedure, from the most disaggregated data available by sector. Data with a certain level of sectoral breakdown was available in the ERIA report for years 2010-2015. This data has been the main data used for building the activity data series used in the sectoral approach of the inventory,

0

1,000

2,000

3,000

4,000

5,000

6,000

Ktoes

Sub‐bitouminous coal Heavy fuel oil Gas/diesel

Fuel oil Motor gasoline Kerosene

LPG Jet fuel Biomass

25

complemented with data from the Ministry of Mines and Energy for the period 2010-2015 and the ASEAN database for years 1995-2012.

The data has been provided primarily in ktoes of fuel consumed and transformed to GJ using the conversion factors provided by the international energy agency6. The following table shows the low calorific value of the fuels, which have been used where appropriate:

Table 15 – Low calorific values of Cambodian fuels

Fuel Low Calorific Content TOE/t TJ/kt

Sub-bituminous coal 0.50 20.76 Additives/Oxygenates 1.21 50.51 Motor gasolina 1.04 43.72 Naphtha 1.05 44.12 Kerosene type jet fuel 1.00 42.03 Kerosene 1.06 44.38 Gas/Diesel oil 1.01 42.35 Fuel oil 1.01 42.17 LPG 0.66 27.78 Lubricants 0.96 40.19 Bitumen 1.00 41.87 Fuelwood & woodwaste 0.37 15.50 Charcoal 0.70 29.31 Electricity 0.09 3.60 Biogas* 50.40

Source: ERIA report, edition 2016. Note –Biogas LHV has been extracted from 2006 IPCC Guidelines.

The emission of the sectoral approach of the energy sector has been estimated using a tier 1 approach for all categories of the energy sector, using fuel-specific emission factors provided by 2006 IPCC guidelines (also EMEP/EEA 2016 Guidelines were used for estimating non-GHG emissions).

In the following sub-sections, information on the activity data, emission factors and emissions obtained for each category included in the sectoral approach of the energy sector is provided in more detail. Subsequently, a comparison between the sectoral approach and reference approach is provided to illustrate the quality of the data used by the inventory.

1A1. Energy Industries

The category 1A1 Energy Industries comprises emissions from fuels combusted by the fuel extraction or energy-producing industries. In Cambodia, energy industry emissions include the emissions which occur in the combustion of fuels for electricity generation as well as the emissions which occur in the manufacture of solid fuels (i.e. production of charcoal). Other

6 Available at https://www.iea.org/statistics/resources/unitconverter/

26

emissions that should be accounted for in this category (such as petroleum refining) do not occur in the country.

Activity data

The following table shows the activity data used for the estimation of emissions:

Table 16 - Activity data energy industries. Data in GJ

Year

Sub-

bituminous

coal

Heavy fuel oil Diesel

Biomass used for the

production of

electricity

Charcoal

Production

1994 0 253 536 386 703 129 372 10 007 289

2005 0 1 482 873 615 567 181 620 14 048 807

2010 727 365 9 784 326 347 730 293 076 10 552 676

2011 832 194 10 212 245 338 491 293 076 9 788 023

2012 1 206 671 9 039 517 464 519 293 076 9 023 370

2013 1 907 466 6 214 607 191 197 167 472 9 408 091

2014 11 693 483 3 522 334 120 182 251 208 9 847 354

2015 24 032 232 2 429 302 82 778 544 284 9 995 269

2016 27 716 616 4 089 326 139 342 586 152 9 995 269

From 2014 there is a significant increase in coal consumption due to the operation of new coal power plants (Sihanoukville 100 MW coal power plant and the first 270 MW coal power plants of the CIIDG Erdos Hongjun Electric Power Co.Ltd.). The increase in coal consumption is reflected in lower levels of heavy fuel oil and diesel consumption.

For coal, the data from ERIA has been used for years 2008-2014 and the Ministry of mines for years 2015 and 2016. In the historical period there was no consumption of coal.

Regarding oil products, ERIA figures should be higher than the figure provided by the Ministry of Mines and Energy, as the data included in ERIA statistics completes the coverage of the data of the Ministry of Mines for years 2010-2015. Nevertheless, the amount of fuel consumed as contained in the data provided by the Ministry of Mines and Energy is higher than the corresponding figures of ERIA. For this reason and aiming at ensuring the consistency of the time series, the inventory has been calculated for this category and years 2010-2015 using the total amount of “oil” consumption from the Ministry of Mines and the split between the different oil products of ERIA. In the historical period there is data available in ASEAN on heavy fuel oil, but there is a sharp decrease in the consumption in years 2008-2009. The series has been smoothed for those years by considering 2008 and 2009 as outliers and interpolating between years 2007-2010.

Methodology and emission factors

The following are the emission factors used for estimating the emissions for the entire time series:

27

Table 17 - Emission factors category 1A1. Energy industries

CO2 CH4 N2O NOx CO NMVOC SOx

Kg/TJ g/GJ Fuel

Coal 96 100 1 1.5 209 8.7 1 820 Heavy fuel oil 77 400 3 0.6 142 15.1 2.3 495 Diesel 74 100 3 0.6 65 16.2 0.8 46.5 Biomass 112 000 30 4 81 90 7.31 10.8Charcoal* NA 1 000 NA NA NA NA NA

Source for GHG: Table 2.2. Chapter 2 Stationary combustion Source for other gases: Tables 3.2 - 3.7, EMEP/EEA 2016 Chapter 1A1 Source for charcoal: Table I-14 IPCC 1996; volumen III for energy

CH4 emissions from the production of charcoal has been estimated using an emission factor from the Revised 1996 Guidelines, as there is no emission factor specific for charcoal production in the 2006 IPCC Guidelines. The emission factor is to be applied to the amount of charcoal produced. This issue will be addressed in the 2019 refinement of the guidelines, so the inventory of Cambodia will consider it in the next inventory submission.

The CO2 emissions of biomass are not included in the total emissions of the sector. CO2 emissions from the consumption of biomass for the production of electricity are estimated by applying the biomass emission factor of the previous table to the amount of biomass consumed. Nevertheless, the CO2 emissions which occur in the production of charcoal cannot be estimated by applying a biomass emission factor to the total amount of firewood used for the production of charcoal, as not all the carbon is combusted in the process. Instead, the carbon content of the biomass is transformed into charcoal. For this reason, the activity data used for calculating CO2 emissions from charcoal is estimated by subtracting the amount of charcoal produced to the total amount of biomass which is used for the production of charcoal. A CO2 emission factor is applied to this amount of biomass calculated as a differential. CO2 emissions from biomass are reported as a memo item.

The remaining emissions are estimated by applying the emission factors to the corresponding activity data.

Results

Table 18 - Emissions in energy industries. Data in Gg

Year CO2 CH4 N2O NOX CO NMVOC SOX 1994 48.28 10.01 0.00 1.22 1.29 0.11 0.30 2005 160.39 14.06 0.00 1.87 1.83 0.15 0.98

2010 852.97 10.59 0.00 4.03 2.90 0.25 5.78 2011 895.48 9.83 0.01 4.22 3.02 0.26 6.10 2012 850.04 9.06 0.01 4.24 3.13 0.26 5.84

2013 678.49 9.43 0.01 4.07 3.20 0.27 5.02 2014 1 405.28 9.88 0.01 5.87 3.39 0.28 11.73 2015 2 503.66 10.04 0.02 8.35 3.56 0.30 21.31 2016 2 990.41 10.05 0.04 9.23 3.47 0.29 25.14

28

CO2 emissions do not include biomass CO2, which is reported as a memory item. The trend of emissions is driven by the decreasing consumption of oil products (diesel and heavy fuel oil) and the significant increase of coal consumption in years 2014-2016.

The emissions of CH4 of the category are strongly driven by the contribution of charcoal production. This effect is not seen in CO2 and N2O emissions, because Co2 is not accounted in the total emissions and N2O emissions from charcoal are not applicable, as specified in the 1996 IPCC Guidelines. The emission trend of these gases is there driven by the increasing consumption of coal for electricity generation.

Figure 8 - Emissions of CO2 in energy industries. Data in Gg

Figure 9 - Emissions of CH4 in energy industries. Data in Gg

0.00

500.00

1,000.00

1,500.00

2,000.00

2,500.00

3,000.00

Gg CO2

CO2

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

16.00

18.00

20.00

Gg CH4

CH4

29

Figure 10 - Emissions of N2O in energy industries. Data in Gg

1A2. Manufacturing Industry and construction

The category 1A2 Manufacturing Industry and construction includes emissions from fuels combusted in industries. If possible, the emissions of this category should be dissagregated by sub-category. The availability of data has not allowed to breakdown the emissions by sub-category. Therefore, the activity and emissions are provided for the manufacturing industry as a whole.

Activity data

Table 19 - Activity data manufacturing industries. Data in GJ

Year Sub-bituminous

coal Fuel oil Diesel LPG Biomass

1994 0 122 877 1 421 414 0 36 638 977 2005 0 718 679 2 221 763 0 33 999 127 2010 211 526 5 191 632 2 763 288 0 27 507 276 2011 246 815 5 400 972 2 888 892 0 28 051 560 2012 270 271 4 856 688 3 223 836 0 30 103 092 2013 278 782 4 103 064 3 098 232 41 868 32 363 964 2014 392 952 2 763 288 3 433 176 41 868 34 624 836 2015 553 620 1 130 436 3 223 836 83 736 37 095 048 2016 711 756 2 058 246 5 869 814 152 462 36 843 840

For coal, the data from the Ministry of Mines and Energy is the same as ERIA for years 2010-2015. Therefore, the data from both sources has been used. For year 2016 there is only data from the Ministry of Mines and Energy. There is no coal consumption for the historical period (before 2010).

0.00

0.01

0.02

0.03

0.04

0.05

Gg N2O

N2O

30

For oil products (fuel oil and diesel) in the manufacturing industry, there is a significant difference between the figures provided by ERIA and the ministry of Mines. The data of ERIA has been used, as it has been considered more complete and more consistent (with the exception of a significant decrease of fuel consumption in year 2015). The data used for year 2016 comes from the Ministry of mines. For the historical period, the interannual variation rate of the data provided by ASEAN on fuel oil and diesel has been applied to year 2010.

For biomass, the data of the ministry of Mines is used for the entire time period. ERIA is supposed to be more complete, but the figures for this specific consumption are lower. Therefore, the inventory has used the data from the Ministry of Mines aiming at being conservative, but this issue should be addressed in the future. For the historical period (data from ASEAN), we split the amount (provided at an aggregated level), between 1A2 and 1A4, using the split of year 2010.

Methodology and emission factors

The following are the emission factors used for estimating the emissions for the entire time series:

Table 20 - Emissions factors in the manufacturing industry.

CO2 CH4 N2O NOx CO NMVOC SOx

Kg/TJ g/GJ

Fuel

Heavy fuel oil 77 400 3 0.6 513 66 25 47

Diesel 74 100 3 0.6 513 66 25 47

Biomass 112 000 30 4 91 570 300 11

Coal 96 100 10 1.5 173 931 88.8 900

Lubricants 73 300 3 0.6 513 66 25 47

LPG 63 100 1 0.1 513 66 25 47

Results

Table 21 - Emissions in the manufacturing industry. Data in Gg

Year CO2 CH4 N2O NOX CO NMVOC SOX

1994 117.14 1.10 0.15 4.08 21.09 11.04 0.58 2005 233.70 1.03 0.14 4.36 20.20 10.32 1.13 2010 724.00 0.89 0.12 4.86 20.70 8.78 5.28 2011 756.82 0.90 0.12 5.02 21.21 8.97 5.51 2012 731.59 0.96 0.13 5.29 21.90 9.54 5.08 2013 653.32 1.02 0.14 5.32 22.48 10.15 4.42 2014 560.35 1.08 0.15 5.49 22.54 10.72 3.35 2015 406.01 1.13 0.15 5.38 22.42 11.31 2.03 2016 710.77 1.14 0.16 6.95 23.32 11.39 3.12

CO2 emissions do not include biomass CO2, which is reported as a memory item. The trend of emissions is driven by the increasing manufacturing industry. The emissions of all gases show

31

a strong increasing trend, along the increasing figures for industrial GDP. Nevertheless, the consistency of the consumption values available for year 2016 shall be ensured in the future. Figure 11 - Emissions of CO2 in energy industries. Data in Gg

Figure 12 - Emissions of CH4 in energy industries. Data in Gg

0.00

100.00

200.00

300.00

400.00

500.00

600.00

700.00

800.00

Gg CO2

CO2

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

1.80

2.00

Gg CH4

CH4

32

Figure 13 - Emissions of N2O in energy industries. Data in Gg

1A3. Transport

The category 1A3 Transport comprises emissions from the combustion and evaporation of fuel for all transport activity (excluding military transport), regardless of the sector. In the Inventory of Cambodia, there are two big sub-categories within the transport sector: civil aviation and road transportation. International bunkers (fuels consumed for international transportation) are not included in the totals but reported separately. Other sub-categories emissions to be allocated here, as railways (not occurrence) and domestic water born navigation (lack of data), have not been estimated in this edition.

Activity data

Table 21 - Activity data air transport. Data in GJ

Year Jet fuel –

International aviation

Jet fuel – Domestic aviation

Motor gasoline

Diesel LPG

1995 473 622 34 655 14 178 229 11 694 366 7 476 2005 851 662 62 317 11 488 989 18 279 058 105 089 2010 1 716 588 125 604 16 412 256 22 734 324 125 604 2011 1 925 928 167 472 16 328 520 28 051 560 460 548 2012 2 428 344 167 472 17 626 428 32 573 304 1 423 5122013 2 847 024 125 604 17 458 956 32 740 776 1 758 456 2014 3 558 780 209 340 19 008 072 34 750 440 2 386 476 2015 3 307 572 251 208 22 357 512 36 927 576 3 642 516 2016 3 307 572 837 360 24 425 173 40 342 701 3 979 382

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

0.20

Gg N2O

N2O

33

The fuel consumption of international aviation is provided separately from domestic aviation, as the emissions of international bunkers are not included in national total GHG emissions.

The data on international aviation is only provided by ERIA. Year 2015 is subrogated to 2016 as there is no information for that year.

For domestic aviation, the data from the ASEAN database is used for the period 1995-2010; for the time period 2010-2015 the data from the Ministry of Mines and Energy is equal to ERIA. Hence, both data sources have been used for this time span. Finally, for year 2016 only data from the ministry of Mines and Energy is available. Regarding this value, as can be noted from the previous table, there is a significant interannual increase in year 2016 which affects the consistency of the time series. This issue needs to be addressed in the future.

For road transport, the data for the period 2010-2015 from ERIA is more disaggregated than the one provided by the ministry of Mines, but the aggregated figures are similar. ERIA has been used for 2010-2015 and the Ministry of Mines and Energy for year 2016, applying the fuel split of the data for year 2015.

For the historical period (ASEAN), there is data directly available for moto gasoline but there is a big gap between series (2010-2016 vs 1995-2009), so the interannual variation rate of the historical series time series (1995-2009) was applied to the figure of 2010 to ensure the consistency of the series. The same approach was followed for diesel. Conversely, the historical series of LPG, provided for the national total (national total consumption of LPG), was split between 1A2 and 1A4 using the proportions of 2010.

Methodology and emission factors

Table 22 - Emission factor in transport category

CO2 CH4 N2O NOx CO NMVOC SOx Kg/TJ

Fuel Jet fuel 71 500 0,5 2 250 28 553 452 24 Motor gasoline 69 300 33 3.2 200 1 937 230 47 Gas/diesel 74 100 3.9 3.9 306 79 17 47 LPG 63 100 62 0.2 547 3 049 491 47 Lubricants 73 300 3 0.6 513 66 25 47

Source for jet fuel GHG: Table 3.6.4 and 3.6.5. chapter Mobile Combustion Source for motor gasoline GHG: Tables 3.2.1 and 3.2. from chapter Mobile Combustion Source for other gases: Tables 3.2 - 3.7, EMEP/EEA 2016 Chapter 1A3

Results

Table 23 - Emissions in the transport sector. Data in Gg

Year CO2 CH4 N2O NOX CO NMVOC SOX 1994 1 852.05 0.51 0.09 6.42 29.40 3.47 1.22 2005 2 161.75 0.46 0.11 7.96 25.80 3.02 1.412010 2 838.89 0.64 0.14 10.33 37.55 4.27 1.85 2011 3 251.22 0.68 0.16 12.14 40.03 4.52 2.11

34

2012 3 736.99 0.80 0.18 14.31 45.83 5.36 2.43 2013 3 755.94 0.81 0.18 14.50 45.35 5.47 2.45 2014 4 057.82 0.91 0.20 15.79 52.81 6.21 2.64 2015 4 533.51 1.11 0.22 17.82 64.50 7.65 2.96 2016 4 993.03 1.21 0.24 19.61 86.54 8.61 3.25

The main driver of GHG emissions in the transport sector is the increased consumption of fuels due to the increasing fleet of private vehicles. This is, in turn, due to the economic development of the country, the demographic expansion and the migration of population from rural to urban areas.

Table 24 - Emissions in international bunkers. Data in Gg

Year CO2 CH4 N2O NOX NMVOC CO SOX 1994 33.86 0.0002 0.0009 0.12 0.21 13.52 0.01 2005 60.89 0.0004 0.0017 0.21 0.39 24.32 0.02 2010 122.74 0.0009 0.0034 0.43 0.78 49.01 0.04 2011 137.70 0.0010 0.0039 0.48 0.87 54.99 0.05 2012 173.63 0.0012 0.0049 0.61 1.10 69.34 0.06 2013 203.56 0.0014 0.0057 0.71 1.29 81.29 0.07 2014 254.45 0.0018 0.0071 0.89 1.61 101.61 0.08 2015 236.49 0.0017 0.0066 0.83 1.50 94.44 0.08 2016 236.49 0.0017 0.0066 0.83 1.50 94.44 0.08

Figure 11 - Emissions of CO2 in Transport. Data in Gg

0.00

500.00

1,000.00

1,500.00

2,000.00

2,500.00

3,000.00

3,500.00

4,000.00

4,500.00

5,000.00

Gg CO2

CO2

35

Figure 12 - Emissions of CH4 in Transport. Data in Gg

Figure 13 - Emissions of N2O in Transport. Data in Gg

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

Gg CH4

CH4

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

Gg N2O

N2O

36

1A4. Other

The category 1A4 Other comprises emissions from the combustion of fuels in other sectors. These sectors are the commercial/institutional sector, the residential sector and the agriculture/forestry/ fishing sector. The inventory of Cambodia includes estimates for all these sectors.

Activity data

Table 25 - Activity data Commerce and public services sector. Data in GJ

Year Kerosene Fuel oil LPG 1994 284 334 9 909 79 749 2005 398 908 57 958 1 120 946 2010 586 152 418 680 1 339 776 2011 293 076 1 004 832 1 256 040 2012 125 604 962 964 711 756 2013 41 868 628 020 753 624 2014 0 334 944 502 416 2015 0 209 340 669 888 2016 0 209 340 669 888

The data from ERIA has been used for the period 2010-2015. For years 1995-2009 for kerosene and fuel oil, the interannual variation rate of the original data from ASEAN has been applied to the value of ERIA of year 2010. It is also worth highlighting that for years 1995-2009 the amount of LPG (which is provided by ASEAN for the national total consumption) is split between categories 1A2 and 1A4 using the proportions of 2010.

As the value for oil consumption from the Ministry of Mines and Energy for year 2016 increases by a factor of 6 compared to the figure of 2015 (fuel oil plus LPG consumption), and would affect the consistency of the time series, the value for year 2016 from this source has not been used. Alternatively, the amount of year 2015 of ERIA has been subrogated to 2016. For future updates of the inventory, this issue should be addressed.

Table 26 - Activity data Residential. Data in GJ

Year Kerosene LPG Biomass

Firewood Charcoal Biogas1994 182 786 17 445 19 394 014 10 007 289 0 2005 256 441 245 207 17 996 669 14 048 807 0 2010 376 812 293 076 23 265 265 10 552 676 101 989 2011 272 142 334 944 24 287 428 9 788 023 131 464 2012 83 736 125 604 25 280 638 9 023 370 114 439 2013 83 736 125 604 26 358 522 9 408 091 30 374 2014 0 167 472 27 589 170 9 847 354 44 430 2015 0 209 340 28 003 550 9 995 269 44 430 2016 0 209 340 28 003 550 9 995 269 44 430

37

For oil products, the figures from the ministry of mines are significantly high compared to ERIA. However, ERIA is generally more robust regarding oil data (see section data sources above for a description of the sources), so the data from ERIA has been used. Nevertheless, this discrepancy between sources should be addressed for future editions of the inventory.

Regarding biomass products, the degree of detail of ERIA is very high compared to the ministry of mines, but the differences of the total amount of biomass consumed between sources (ERIA vs Ministry of Mines) are significant. The data from ERIA has been used for years 2010-2015 and for year 2016, when the data was subrogated. Even within the statistics provided by ERIA there are also differences in the data provided at different level of aggregation. The data provided at the most disaggregated level in the ERIA statistics has been used in the inventory.

For the historical period (1995-2019), the biomass fuel consumption provided by ASEAN is differentiated by “charcoal” and “firewood” and is not allocated in sectors. Therefore, the firewood quantities provided have been split between categories 1A4 and 1A2 using the proportions of 2007. For charcoal, it was assumed that the figures provided for the historical series is charcoal production, and all charcoal was consumed in the residential sector.

Lastly, biogas data was compiled in the ERIA statistics and was originally gathered by the national biodigester program, which started in year 2007. For future editions of the inventory, the data gathering collection process for biomass within the Ministry of Mines and Energy could be improved by using the same disaggregation as the ERIA statistics.

Table 27 - Activity data agriculture. Data in GJ

Year Diesel

1994 689 1712005 1 077 219 2010 1 339 776 2011 1 590 984 2012 1 842 192 2013 1 758 456 2014 2 093 400 2015 1 590 984 2016 1 590 984

Methodology and emission factors

Table 28 - Emission factors used for the Commercial and institutional sub-sectors

CO2 CH4 N2O NOx CO NMVOC SOx Kg/TJ

Fuel Kerosene 71 900 10 0.6 51 57 0.7 70 Fuel oil 77 400 10 0.6 51 57 0.7 70LPG 63 100 5 0.1 51 57 0.7 70

Source for jet fuel GHG: Table 3.6.4 and 3.6.5. chapter Mobile Combustion Source for GHG: Table 2.2. Chapter 2 Stationary combustion Source for other gases: Tables 3.1 - 3.5, EMEP/EEA 2016 Chapter 1A14

38

Table 29 - Emission factors used for the Residential and agricultural sub-sectors

CO2 CH4 N2O NOx CO NMVOC SOx

Kg/TJ Fuel

Kerosene 71 900 10 0.6 51 57 0.7 70 LPG 77 400 10 0.6 51 57 0.7 70Gas/diesel 74 100 10 0.6 51 57 0.7 70 Firewood 112 000 300 4 91 570 300 11 Charcoal 112 000 200 1 91 570 300 11Biogas 54 600 5 0.1 74 29 23 0.67

Source for GHG: Table 2.2. Chapter 2 Stationary combustion Source for other gases: Tables 3.1 - 3.5, EMEP/EEA 2016 Chapter 1A14 Air quality gases EFs for firewood and charcoal extracted from table 3.10 Air quality gases EFs for biogas extracted from table 3.8

Results

Table 30 - Emissions in the other sectors. Data in Gg

Year CO2 CH4 N2O NOX NMVOC CO SOX

1994 83.97 7.83 0.09 2.74 8.82 16.83 0.41 2005 205.78 8.23 0.09 3.08 9.62 18.45 0.57 2010 289.22 9.22 0.21 12.58 40.75 77.66 1.802011 319.20 9.41 0.24 15.31 49.67 94.63 2.15 2012 258.66 9.53 0.23 13.73 44.63 85.00 1.91 2013 224.08 9.84 0.15 6.19 19.84 37.89 0.96 2014 200.29 10.31 0.17 7.61 24.56 46.84 1.12 2015 172.07 10.46 0.17 7.64 24.73 47.14 1.09 2016 172.07 10.46 0.17 7.64 24.73 47.14 1.09

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Figure 14 - Emissions of CO2 in other sectors. Data in Gg

Figure 15 - Emissions of CH4 in other sectors. Data in Gg

0.00

50.00

100.00

150.00

200.00

250.00

300.00

Gg CO2

CO2

0.00

2.00

4.00

6.00

8.00

10.00

Gg CH4

CH4

40

Figure 16 - Emissions of N2O in other sectors. Data in Gg

3.3.4. Comparison between the Reference and Sectoral Methods

IPPC guidelines recommend applying a Sectoral approach and a Reference approach to estimate country’s CO2 emissions from fuel combustion and to compare the results of these two independent estimates. The Sectoral approach uses values bounded to each category that together add up the national total of the Energy sector while the Reference approach uses the total values of the national energy statistics.

The Reference approach is a top-down approach, using a country’s energy supply data to calculate the emissions of CO2 from combustion of mainly fossil fuels. Therefore, the Reference approach is designed to calculate the emissions of CO2 from fuel combustion, starting from high level energy supply data.

The assumption is that carbon is conserved so that, for example, carbon in crude oil is equal to the total carbon content of all the derived products.

The Reference approach does not distinguish between different source categories within the energy sector and only estimates total CO2 emissions from Source category 1A, Fuel Combustion.

For estimating CO2 emissions using the reference approach, the following 5 steps methodology needs to be followed:

Step 1: Estimate Apparent Fuel Consumption in Original Units Step 2: Convert to a Common Energy Unit Step 3: Multiply by Carbon Content to Compute the Total Carbon Step 4: Compute the Excluded Carbon

0.00

0.05

0.10

0.15

0.20

0.25

0.30

Gg N2O

N2O

41

Step 5: Correct for Carbon Unoxidized and Convert to CO2 Emissions

These steps are expressed in the following equation:

𝑪𝑶𝟐 𝑨𝑪𝒇𝒖𝒆𝒍 ∗ 𝑪𝑭𝒂𝒄𝒕𝒐𝒓𝒇𝒖𝒆𝒍 ∗ 𝑪𝑪𝒇𝒖𝒆𝒍 ∗ 𝟏𝟎 𝟑 𝑬𝑪𝒂𝒓𝒃𝒐𝒏𝒇𝒖𝒆𝒍 ∗ 𝑪𝑶𝑭𝒇𝒖𝒆𝒍𝒂𝒍𝒍 𝒇𝒖𝒆𝒍𝒔

∗ 𝟒𝟒/𝟏𝟐

Where:

AC= Apparent Consumption = production + imports – exports – international bunkers – stock change CFactor = conversion factor for the fuel to energy units (TJ) on a net calorific value basis CC = carbon content (tonne C/TJ (= kg C/GJ) ) ECarbon = carbon in feedstocks and non-energy use excluded from fuel combustion emissions (Gg C)

The data used for calculating the reference approach is the energy balance provided by the Ministry of Mines and Energy. The differences between the sectoral and reference approach are the following:

Table 31 – Differences between the sectoral and reference approaches (%)

2010 2011 2012 2013 2014 2015 2016 6.01 3.41 6.05 0.88 0.57 7.34 7.73

There was no official energy balance before year 2010. The sectoral approach uses the most disaggregated data available that for years 2010-2015 is generally available in ERIA statistics.

The data sources used in both approaches (ERIA statistics and the energy balance form the ministry of Mines) are official. Nevertheless, no information is available to explain these differences between data sources. The data from ERIA statistics is more disaggregated and was found to be more consistent than the data from the Ministry of Mines. For this reason, it is the main data source used by the inventory. For the future, Cambodia will need to address the improvement of its energy statistics and ensure the consistency of the fuel consumption data. For years 2010 and 2012 the difference is found in solid fuels, while for years 2015 and 2016 the difference is encountered in liquid fuels. A detailed explanation of the inconsistencies found between data sources is provided at category level in the methodological section of the inventory.

3.3.5. Energy emissions trend

In the time span covered by the inventory, Cambodian GDP has experienced a significant expansion, along its population. This is reflected in the increasing trend of the emissions of the Energy sector. The energy demand has experienced a significant increase, transport sector is expanding, and the population is migrating to cities; all these factors combined led to increasing fuel consumption and higher GHG emissions in the energy sector.

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Table 32 - Trend of emissions (GHG, Gg CO2-eq)

Inventory Sector 1994 2000 2005 2010 2015 2016 1A1. Energy Industries 298.87 450.75 512.49 1 120.27 2 766.58 3 255.58 1A2. Manufacturing Industry 188.73 242.25 300.79 781.84 479.92 785.59 1A3. Transport 1 892.04 2 003.53 2 205.42 2 897.00 4 625.81 5 094.21 1A4. Other 305.89 401.64 437.32 581.34 483.26 501.19 Total 2 685.53 3 098.17 3 456.03 5 380.45 8 355.57 9 636.58

Figure 17 – GHG emissions in the energy sector - 1994-2016 (Gg CO2-eq)

As illustrated in the figure above, the main contributor to energy sector emissions is transport (category 1A3), with a contribution that ranges from a 70.5% in 1994, to a 52.9% in 2016. The second contributor to GHG emissions of the energy sector is energy industries (category 1A1), with a contribution that ranges from a 11.1% in 1994 to a 33.8% in 2016.

The sharp interannual variation of emissions in the energy industry in year 2013 is due to the effect produced by the trade-off in electricity production from oil products to coal (a sharp decrease in oil products consumption were registered in 2013, while coal consumption only starts to raise in year 2014, producing this fall in consumption in year 2013) added to an overall slowdown in fuel consumption produced this year. The third contributor to the emissions is the sector other (category 1A4), with a contribution that ranges from a 11.4% in 1994 to a 5.2% in 2016. Lastly, the manufacturing and construction industry contributes with a 7.0% of emissions in 1994 and increased up to 8.2 in year 2016. The following table shows the contribution of each category to the energy GHG emissions for the entire time period.

0.00

2,000.00

4,000.00

6,000.00

8,000.00

10,000.00

12,000.00

Gg Co2‐eq

1A4 Other ‐ Total 1A3 Transport ‐ Total 1A2 Manufacturing Industry 1A1 Energy Industries

43

Table 33 - Percentage of contribution to energy GHG emissions by category

Inventory Sector 1994 2000 2005 2010 2015 2016 1A1. Energy Industries 11.1% 14.5% 14.8% 20.8% 33.1% 33.8%1A2. Manufacturing Industry 7.0% 7.8% 8.7% 14.5% 5.7% 8.2%1A3. Transport 70.5% 64.7% 63.8% 53.8% 55.4% 52.9%1A4. Other 11.4% 13.0% 12.7% 10.8% 5.8% 5.2%Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

Regarding the contribution of each gas to total GHG emissions, the following table show the detailed evolution of the split of greenhous gases for the entire time period.

Table 34 - Percentage of emissions by gas

Inventory Sector 1994 2000 2005 2010 2015 2016 CO2 78.3% 76.3% 79.9% 87.4% 91.1% 92.2% CH4 18.1% 20.3% 17.2% 9.9% 6.8% 5.9% N2O 3.6% 3.4% 2.9% 2.6% 2.1% 1.9% Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

Note – This contribution is calculated converting first the emissions of each gas to CO2‐eq using global warming 

potentials 

The gas which is predominant in the sector is CO2, followed by CH4. The lower contribution of CH4 is explained by the decreasing contribution of biomass to total energy consumption, which in turn produces an increase in the contribution of CO2. This effect is intesified in the last period of the series by the increase of coal consumption for production of electricity.

Apart from GHG, the estimates of the energy sector included GHG precursors, which has been calculated using the EMEP/EEA guidelines. The following figure shows the temporal evolution of the emissions estimated for all gases, including precursors.

Table 35 - Emissions by gas (Gg)

Inventory Sector 1994 2000 2005 2010 2015 2016 CO2 2 101.44 2 363.53 2 590.02 4 705.08 7 615.25 8 866.28 CH4 19.46 25.21 25.09 21.34 22.74 22.87 N2O 0.33 0.35 0.36 0.48 0.58 0.61 NOx 14.46 16.70 17.69 31.80 39.20 43.43 CO 68.62 69.85 68.25 138.80 137.61 160.46

NMVOC 23.44 25.22 24.82 54.04 43.99 45.03 SO2 2.51 3.15 3.26 14.71 27.40 32.61

44

3.3. Industrial Processes and Product Use (IPPU) sector 3.4.1. Characterization of the sector

The industrial Processes and Product Use (IPPU) sector includes the emissions which occur in the production and the consumption of products, except those due to the combustion of fuels, which are included in the energy sector, and the generation and treatment of waste, which are included in the waste sector. Considering that exclusion, GHG emissions are produced from a wide variety of industrial activities. The main emission sources are releases from industrial processes that chemically or physically transform materials where many different GHG, including carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), hydrofluorocarbons (HFCs) and perfluorocarbons (PFCs), are produced during these processes. Based on the 2006 IPCC Guidelines, the IPPU sector comprises eight categories:

2.A - Mineral Industry 2.B - Chemical Industry 2.C - Metal Industry 2.D - Non-Energy Products from Fuels and Solvent Use 2.E - Electronics Industry 2.F - Product Uses as Substitutes for Ozone Depleting Substances 2.G - Other Product Manufacture and Use 2.H – Other

Nevertheless, the information available in the country points out that in Cambodia only the production of cement, the consumption of lubricants and the use of fluorinated gases occur. Consequently, the inventory includes emissions estimates for 2.A.1 Cement Production, 2.D.1 Lubricant Use, 2F1 Refrigeration and Air Conditioning and 2.F.3 Fire Protection.

Aiming at providing an overview of the industrial structure of the country, the following table shows the percentual contribution of each economic sector to national total Gross Domestic product (GDP).

Table 36 – GDP distribution by economic sector – Cambodia, 2016

Sector/subsector Percentage of total GDP Agriculture 25% Services 40% Other 7% Industry 29%

Mining 3.21% Manufacturing 33.65%

Food, Beverages & Tobacco 4.86% Textile,Wearing Apparel & Footwear 22.15% Wood, Paper & Publishing 1.08% Rubber Manufacturing 1.17% Other Manufacturing 4.39% Non-Metallic Manufacturing 1.12% Basic Metal and Metal Products 0.63% Other manufacturing 2.64%

Electricity, Gas & Water 1.17% Construction 23.94%

Source: own elaboration based on https://www.nis.gov.kh/nis/NA/NA2016_Tab.htm

45

The data available on the production and consumption of products in the country is scarce. This has been a significant challenge for estimating the emissions of this category. This is, in fact, the reason for not estimating the emissions of NMVOC, which are potentially a big source of indirect GHG emissions, given the industrial characteristics of the country.

The following table provides a summary of the emissions for the energy sector in year 2016. A complete reporting table is provided in the section Reporting tables.

Table 37 - Sectoral reporting table – IPPU sector –GHG emissions of year 2016

GREENHOUSE GAS SOURCE AND SINK

CATEGORIES CO2 CH4 N2O HFCs PFCs SF6 NF3 NOx CO NMVOC SO2

Total industrial processes

1449.46 NA, NE, NO

NA, NE, NO

371.68 NA, NE, NO

NA, NE, NO

NA, NE, NO

NA, NE, NO

NA, NE, NO

NE, NO NA, NE, NO

A. Mineral industry 1420.96 NA NA NA NA

1. Cement production 1420.96

2. Lime production NE

3. Glass production NE 4. Other process uses of carbonates NE NA NA NA NA

B. Chemical industry NA, NO NA, NO NA, NO NA, NO NA, NO NA, NO NA,

NO NA, NO NA, NO NA, NO

NA, NE, NO

C. Metal industry NE, NO NE, NO NO NO NO NO NO NE, NO NE, NO NE, NO NE,

NO D. Non-energy products from fuels and solvent use

NA, NE NA, NE NA, NE NA NA NE NE

1. Lubricant use 28.50 NE NE NA NA NE NA

2. Paraffin wax use NE NE NE NA NA NE NA

3. Other NA NA NA NA NA NE NA

E. Electronics industry NE, NO NE, NO NE, NO NE, NO

F. Product uses as substitutes for ODS(2)

371.68 NA, NE, NO NA, NO NA,

NO

1. Refrigeration and air conditioning 371.50 NE NA NA

2. Foam blowing agents NO NA NA NA

3. Fire protection 0.19 NE NA NA

4. Aerosols NO NA NA NA

5. Solvents NO NO NO NO

6. Other applications NO NO NO NO G. Other product manufacture and use

NO NO NO NA, NO NA, NO NA, NO NA, NO NO NO NO NO

H. Other (as specified in tables 2(I).A-H and 2(II))(3)

NE NA NA NA NA NA NA NA NA NE NA

Note: NO: not occurring NA: not applicable NE: not estimated

46

3.4.2. Data sources

The table 38 below summarises the information used for the estimation of emission in the IPPU sector:

Table 38 - IPPU source of information

Source of information Description of information Ministry of Industry and Handicraft Production data for years 2014-2017

Different sources compiled by the national team Cement Production capacity and year of installation

One cement production company Production data from one cement production plant

Cambodia Energy Statistics – ERIA and the Ministry of Mines and Energy. Fuel consumption data

The National Ozone Unit Ministry of Environment the Royal Government of Cambodia CAMBODIA HFC INVENTORY

3.4.3. Industrial emissions by category

2A. Mineral Industry

This category includes the CO2 emissions due to the consumption of carbonates in the production and use of mineral industrial products. As described by IPCC 2006, There are two broad pathways for release of CO2 from carbonates: calcination and the acid-induced release of CO2. In Cambodia, we will find only emissions due to calcination. A typical calcination reaction would be the following:

CaCO3 + Heat CaO + CO2

CO2 emissions from calcination of carbonates are mainly produced in three industrial activities: i) cement production, ii) lime production, and iii) glass production. Other industrial activities with lower significance are the production of ceramics, soda ash and magnesite production. According to this differentiation, IPCC 2006 Guidelines proposes the following categories for estimating CO2 emissions due to calcination of carbonates: 2A1 Cement production, 2A2 Lime production, 2A3 Glass production and 2A4 other uses of carbonates.

The methodologies for the estimation of the emissions in the four categories are based on the same methodological principle: the characterisation of the carbonates calcined with the objective of calculating stoichiometrically the CO2 release to the atmosphere. The molecular weight of the reagents and products of the calcination will produce the emission factor for each case. In the case of the typical calcination reaction {1}, the stoichiometric emission factor for CaCO3 will be ~ 44 tCO2/t Carbonate consumed:

CaCO3 + Heat CaO + CO2 Molecular Weight: [40 + 12 + 16x3] [40 + 16] + [12 + 16 x2]

100 56 + 44 For the inventory, only the production of cement has been identified as occurring in the country. The completeness of the sector will need to be further assessed in the future.

47

Cement production

In cement manufacture, CO2 is produced during the production of clinker, a nodular intermediate product that is then finely ground, along with a small proportion of calcium sulfate [gypsum (CaSO4·2H2O) or anhydrite (CaSO4)], into hydraulic (typically Portland) cement. During the production of clinker, limestone, which is mainly calcium carbonate (CaCO3), is heated, or calcined, to produce lime (CaO) and CO2 as a by-product (as in the expression above).

Additionally, cement kiln dust (CKD) may be generated during the manufacture of clinker. Emission estimates should account for emissions associated with the CKD.

Activity data

The data used for the estimation of the cement production emissions consist on:

i) national total cement production; and ii) clinker and cement production from the biggest producer company in the country.

The information of the production plant is not presented in this report for confidentiality reasons.

It is worth highlighting that 100% of national cement production is covered by the production plant which provided information for the period 2007-2015. In 2016, however, not all cement production is covered by the production of this plant. No information was available on cement production before 2007.

Table 39 - Activity data cement production. Data in tonnes

Year National total cement production

2007 86 899 2008 772 029 2009 737 326 2010 814 105 2011 947 471 2012 1 071 899 2013 1 117 3362014 1 161 633 2015 1 389 880 2016 3 034 231

48

Methodology and emission factors

The methodology followed is a combination of the tier 1 and tier 2 approaches of 2006 IPCC. First, the clinker production provided by the biggest production plant is used for calculating CO2 emissions using the tier 2 approach. The following equation illustrates the method followed:

𝐶𝑂 𝐸𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑠 𝑀 ∗ 𝐸𝐹 ∗ 𝐶𝐹

Where:

Mcl = weight (mass) of clinker produced, tonnes EFcl = emission factor for clinker, tonnes CO2/tonne clinker CFckd = emissions correction factor for CKD, dimensionless

Then, as the information provided by the production plant included both cement and clinker production, the amount of cement not covered by the production plant was calculated by subtracting the production of the plant from the total national production. Using this quantity as activity data, the tier 1 method was applied, as follows:

𝐶𝑂 𝐸𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑠 𝑀 ∗ 𝐶 𝐼𝑚 𝐸 ∗ 𝐸𝐹

Where: Mcl = weight (mass) of cement produced of type i, tonnes Ccli = clinker fraction of cement of type i, tonnes Im = imports for consumption of clinker, tonnes Ex = esports of clinker, tonnes EFclc = emission factor for clinker in the particular cement, tonnes CO2/tonne clinker. The default EFclc is corrected for CKD CFckd = emissions correction factor for CKD, dimensionless

The emission factor used was the default tier 1 emission factor, which is already corrected for CKD: 0.52 tonnes CO2/tonne clinker.

The clinker fraction used for the cement production not covered by the production plan which provided information on clinker was the default provided by IPCC: 95%.

49

Results Table 40 - Emissions in cement production. Data in Gg

Year CO2 (Gg) 1994 0 2005 0 2010 370.14 2011 430.89 2012 486.722013 507.13 2014 510.49 2015 652.89 2016 1 420.96

The high increase in CO2 emissions in 2016 is explained by the commissioning of a new cement plant in 2015. In 2018 an additional plant has been inaugurated, so the increasing trend in CO2 emissions from cement production is expected to continue in the future.

Figure 18 - Emissions of CO2 in cement production. Data in Gg

50

2D1. Lubricants

Lubricants are mostly used in industrial and transportation applications. Lubricants are produced either at refineries through separation from crude oil or at petrochemical facilities. The use of lubricants in engines is primarily for their lubricating properties and associated emissions are therefore considered as non-combustion emissions to be reported in the IPPU Sector. However, in the case of 2-stroke engines, where the lubricant is mixed with another fuel and thus on purpose co-combusted in the engine, the emissions should be estimated and reported as part of the combustion emissions in the Energy Sector. In this edition of the inventory all the lubricants consumed in the country are considered as non-energy consumption and reported in the IPPU, consistently with the information provided in the energy balances of the country.

Activity data

The data used for the estimation of lubricant emissions consist on national total lubricant consumption from the energy balance developed by the ministry of Mines and Energy and ERIA (see the energy sector for additional information). Due to the unavailability of data, the information of year 1995 has been subrogated for obtaining the activity data and emissions of year 1994.

Table 40 - Activity data lubricant consumption. Data in tonnes

Year Lubricant consumption (TJ)

1994 259.58 2005 437.10 2010 586.15 2011 795.49 2012 711.76 2013 795.49 2014 586.152015 1 925.93 2016 1 943.39

The increase of activity data of lubricants in the last years of the time series is due to a very significant increase in the lubricants used in the transport sector, which reflects the economic development (increased per capita income rates) of the country. The order of magnitude of this data and the time series consistency will need to be ascertained in future inventory editions.

51

Methodology and emission factors

The tier 1 approach of 2006 IPCC guidelines has been used, as follows:

𝑪𝑶𝟐 𝑬𝒎𝒊𝒔𝒔𝒊𝒐𝒏𝒔 𝑳𝑪 ∗ 𝑪𝑪𝑳𝒖𝒃𝒓𝒊𝒄𝒂𝒏𝒕 ∗ 𝑶𝑫𝑼𝑳𝒖𝒃𝒓𝒊𝒄𝒂𝒏𝒕 ∗ 𝟒𝟒/𝟏𝟐 Where:

LC = total lubricant consumption, TJ CCLubricant = carbon content of lubricants (default), tonne C/TJ (=kg C/GJ) ODULubricant = ODU factor (based on default composition of oil and grease), fraction 44/12 = mass ratio of CO2/C

This equation has been applied using a Lubricant Carbon Content (tonne-C/TJ) of 20, and a Fraction Oxidized During Use (ODU factor) of 0.2.

Results

Table 41 - Emissions in lubricants category. Data in Gg

Year CO2 (Gg)1994 3.81 2005 6.41 2010 8.60 2011 11.67 2012 10.44 2013 11.672014 8.60 2015 28.25 2016 28.50

The increasing trend of emissions of lubricants is driven by the increasing consumption, which is in turn due to the demographic and economic expansion of the country. The significant increase of lubricants in the last years of the series is due to a very significant increase in the lubricants used in the transport sector.

2F - Substitutes for Ozone Depleting Substances (F-gases)

Hydrofluorocarbons (HFCs), perfluorocarbons (PFCs) and other fluorinated gases are serving as alternatives to ozone depleting substances (ODS) being phased out under the Montreal Protocol. The sectors in which HFC, PFC and other fluorinated gases are used are the following:

• refrigeration and air conditioning; • fire suppression and explosion protection; • aerosols; • solvent cleaning; • foam blowing; and • other applications.

52

HFCs and PFCs have high global warming potentials and are acquiring importance at international level regarding their contribution to national totals of GHG emission inventories. In this edition of the inventory, HFC emissions of the categories refrigeration and air conditioning and fire protection have been estimated.

Activity data

The activity data of this category is obtained from a study carried out by The National Ozone Unit of the Ministry of Environment on Hydrofluorocarbons (HFC) consumed in the country. The information is limited to the imports of gases.

Table 42 - Activity data of refrigeration - Imports of gases (tonnes)

Year HFC-125 HFC143a HFC134a

2012 1.38 1.63 5.58 2013 1.19 1.41 7.00 2014 3.15 3.57 8.77 2015 2.35 2.72 10.79 2016 2.41 2.79 11.06

Table 43 - Activity data of air conditioning - Imports of gases (tonnes)

Year HFC-125 HFC134a HFC-32

2012 4.75 260.56 4.74 2013 6.20 269.64 6.16 2014 14.30 303.85 14.26 2015 15.98 317.38 15.94 2016 16.38 325.32 16.34

Table 44 - Activity data of fire protection- Imports of gases (tonnes)

Year HFC-227ea

2012 0.000 2013 0.000 2014 0.080 2015 0.080 2016 0.082

Methodology and emission factors

The tier 1 approach provided by 2006 IPCC Guidelines has been followed by using the worksheets provided along with the guidelines available at: https://www.ipcc-nggip.iges.or.jp/public/2006gl/vol3.html

The main assumptions taken and default coefficients used for the estimation of the emissions are illustrated in the following table:

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Table 45 - The main assumptions taken and coefficients used

Year of Introduction of the gases 2005

Growth Rate in New Equipment Sales 2.5%

Assumed Equipment Lifetime (years) 10

Emission Factor from installed base 15%

% of gas destroyed at End-of-Life 25%

The data which was made available to the inventory team consisted in imports of refrigerant products (blends). In order to obtain the activity data of each gas by category, the gas composition of blends provided by IPCC has been used to convert the data, as follows:

Table 46 - Gas composition of blends

Gas blend HFC-125 HFC143a HFC134a HFC-32 Total

R-404A 44% 52% 4% 1 R-507A 50% 50% 1 R-410A 50% 50% 1 R-407C 25% 52% 23% 1

Source: table 7.8 chapter 7, volumen 2 IPPU, IPCC 2006 

Results

Table 47 - HCF’s Emissions. Data in Gg CO2-eq

Year HFC-125 HFC143a HFC134a HFC-32 HFC-227ea

1994 0 0.000 0.000 0 0 2005 0.15 0.12 6.00 0.050 0.003 2010 2.75 2.08 108.31 0.910 0.056 2011 3.58 2.70 140.79 1.183 0.073 2012 4.49 3.39 176.76 1.486 0.091 2013 5.07 3.83 209.58 1.887 0.111 2014 7.62 5.65 245.20 3.047 0.133 2015 9.46 7.02 299.23 4.376 0.162 2016 11.08 8.22 346.65 5.543 0.188

There has been a threefold increase in the consumption of HFCs gases. The most used gas is HFC134a, the HFC which is more used at international level in these applications. The increase in the consumption of gases has been driven by the expansion of the services sector (tourism).

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Figure 19 - HFC emissions – data in Gg of CO2-eq

3.4.4. IPPU emissions trends

Table 48 - Trend of emissions (GHG, Gg CO2-eq)

Inventory Sector 1994 2000 2005 2010 2015 2016 2A1. Cement production NO NO NO 370 653 1,421 2D1. Lubricants 3.81 6.04 6.41 8.60 28.25 28.50 2F. Subst. for ODS (F-gases) NO NO 6.32 114.10 320.24 371.68

Total 3.81 6.04 12.73 492.84 1 001.38 1 821.15

Table 49 - Emissions by gas (Gg)

Inventory Sector 1994 2000 2005 2010 2015 2016

CO2 3.81 6.04 6.41 378.74 681.14 1 449.46 CH4 NA NA NA NA NA NA N2O NA NA NA NA NA NA HFC NO NO 6.32 114.10 320.24 371.68 NOx NA NA NA NA NA NA CO NA NA NA NA NA NANMVOC NE NE NE NE NE NE SO2 NA NA NA NA NA NA SF6 NA NA NA NA NA NA

0

50

100

150

200

250

300

350

400

Gg CO2‐eq

HFC‐125 HFC143a HFC134a HFC‐32 HFC‐227ea

55

Figure 20- GHG emissions in the IPPU sector– data in Gg of CO2-eq

3.5. AFOLU sector 3.5.1. Characterization of the sector

AFOLU sector (Agriculture, forestry and other Land Uses), in Cambodia is very impacted by the land use part (category 3.B). For the period after 2010 especially, large emissions (131011 Gg CO2eq/yr) are estimated on the basis of changes measured between 2010 and 2014. Indeed, emissions largely exceeds removals for this category. In agriculture, rice cultivations and enteric fermentation are the main sources with respectively 9856 Gg CO2eq/yr and 3 554 Gg CO2eq/yr.

3.5.2. Data sources

The main data sources for agriculture are national statistics from the Ministry of Agriculture, Forestry and Fisheries (MAFF). It concerns animal populations, crop areas and productions.

Data on fertilizers is estimated thanks to statistics from the Ministry of Commerce (MoC). This data was completed by data estimated by the FAO and provided on FAOSTAT.

For the land use categories all the data used is coming from the report on forest reference level (FRL) provided by Cambodia to the UNFCCC within the REDD+ framework.

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3.5.3. AFOLU emissions by category

3.A – Livestock Activity data

All emissions from livestock are based on animal populations. The animal populations are estimated based on different references. Data from 1990-2007 is from Statics Yearbook 2008, data from 2009-2017 is from Annual Report of the General Directorate of Livestock and Livestock Production reports from the Ministry of Agriculture, Forestry and Fisheries (MAFF). Data for the year 2008 is estimated by linear interpolation between 2007 and 2009. Animal population of horses, sheep goats are extrapolated from 1990 to 2009 because of missing data. The category of poultry only includes chicken and ducks which are the main poultry production in Cambodia (pigeons, quails and geese are neglected). Table 50 - Activity data - Animal populations (heads)

Year Cattle Buffaloes Pigs Poultry Horses Sheep Goats

1990 2181000 736000 1515000 8163000 7682 689 23987 1991 2257100 755300 1550000 8816200 7682 689 23987 1992 2468000 804000 2043000 9901000 7682 689 23987 1993 2542010 823700 2122700 10692400 7682 689 23987 1994 2620905 809200 2024178 10017100 7682 689 23987 1995 2785725 764808 2043629 10062364 7682 689 23987 1996 2761823 743928 2151097 11411698 7682 689 23987 1997 2820783 693662 2438313 12098035 7682 689 23987 1998 2679928 693651 2339168 13116990 7682 689 23987 1999 2769420 653910 2189358 13417480 7682 689 23987 2000 2992670 693650 1933950 15249770 7682 689 23987 2001 2868830 626020 2114540 15248450 7682 689 23987 2002 2924480 625929 2105440 16678150 7682 689 23987 2003 2985300 660390 2304130 16013600 7682 689 23987 2004 3039939 710143 2428566 12990592 7682 689 23987 2005 3193146 676646 2688612 15085547 7682 689 23987 2006 3344742 724378 2740815 15135065 7682 689 23987 2007 3368449 772780 2389389 15825314 7682 689 23987 2008 3464691 750251 2257847 16176012 7682 689 23987 2009 3560932 727722 2126304 16514244 7682 689 23987 2010 3484481 702074 2057431 20543509 12468 613 10547 2011 3406967 689829 2099332 21307292 12573 346 11592 2012 3369790 656942 2208611 22834809 12312 215 11239 2013 3430895 619114 2454426 27316415 7119 100 12856 2014 3053537 541827 2360823 25461910 9078 238 16454 2015 2903421 506166 2357839 26506407 7486 378 21489 2016 2897126 523320 2371283 28230663 5610 400 22719

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3.A.1 - Enteric Fermentation

Methodology and emission factors

Emissions from enteric fermentation are estimated with the tier 1 methodology from the 2006 IPCC guidelines according to these equations:

𝐸𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑠 𝐸𝐹 ∗ 𝑁

10

Where: Emissions = methane emissions from Enteric Fermentation, Gg CH4 yr-1 EF(T) = emission factor for the defined livestock population, kg CH4 head-1 yr-1 N(T) = the number of head of livestock species / category T in the country T = species / category of livestock

𝑇𝑜𝑡𝑎𝑙 𝐶𝐻 𝐸

Where: Total CH4Enteric = total methane emissions from Enteric Fermentation, Gg CH4 yr-1 Ei = is the emissions for the ith livestock categories and subcategories

Emission factors are default values proposed by the 2006 IPCC guidelines for Asia and developing countries in tables 10.10 and 10.11. Table 51 - Emission factors for enteric fermentation – kg CH4/head/year

Cattle Buffaloes Pigs Poultry Horses Sheep Goats 47 55 1 0 18 5 5

Results

Table 52 - Emission from enteric fermentation

Year 1994 2000 2005 2010 2015 2016 CH4 (Gg/year) 170 181 190 205 167 168

3.A.2 - Manure Management

Methodology and emission factors for CH4

CH4 emissions from manure management are estimated with the tier 1 methodology from the 2006 IPCC guidelines according to this equation:

𝐶𝐻 𝐸𝐹 ∗ 𝑁

10

58

Where: CH4Manure = CH4 emissions from a manure management, for a defined population, Gg CH4 yr-1 EF(T) = emission factor for the defined livestock population, kg CH4 head-1 yr-1 N(T) = the number of head of livestock species / category T in the country T = species / category of livestock

CH4 emission factors are default values proposed by the 2006 IPCC guidelines for Asia and developing countries with a warm climate in tables 10.14 and 10.15.

Table 53 - Emission factors for manure management – kg CH4/head/year

Cattle Buffaloes Pigs Poultry Horses Sheep Goats Elephants 1 2 7 0.02 2.19 0.2 0.22 0

The equations for tier 2 methodology proposed in the IPCC guidelines were also implemented with the default values proposed for manure management systems and logically, the emissions factors were like the ones proposed by the tier 1 methodology.

Results for CH4

Table 54 - Emission from manure management

Year 1994 2000 2005 2010 2015 2016 CH4 (Gg/year) 19 18 24 20 21 21

Methodology and emission factors for N2O

N2O emissions from manure management are estimated with the tier 1 methodology from the 2006 IPCC guidelines according to this equation:

𝑁 𝑂 𝑁 ∗ 𝑁𝑒𝑥 ∗ 𝑀𝑆 , ∗ 𝐸𝐹 ∗ 4428

Where: N2OD(mm) = direct N2O emissions from a manure management in the country, Kg N2O yr-1 N(T) = number of head of livestock species/category T in the country Kg N animal yr-1 MS(T,S) = fraction of total amount nitrogen excretion for each livestock species/category T that is managed

in manure management system S in the country, dimensionless EF3(S) = emission factor for the direct N2O emissions from manure management system S in the country,

Kg N2O-N/kg N in manure management system S

S = manure management system T = species / category of livestock 44/28 = conversion of (N2O-N)(mm) emissions to N2O(mm) emissions

All parameters used in the calculations are default values proposed by IPCC guidelines for Asia: animal weights (TAM), nitrogen excretion rates (Nrate) and manure management systems.

59

Table 55 - Nitrogen excretion rates and animal weights

Variable\Animal Cattle Buffaloes PigsPoultr

y Horses Sheep Goats

Nrate (kg N / 1000 kg animal/day) 0.34 0.32 0.5 0.82 0.46 1.17 1.37

TAM (kg/animal) 319 380 28 1.8 238 28 30 Nex (kg N/animal/year) 39.6 44.4 5.1 0.5 40.0 12.0 15.0

Table 56 - Manure management systems used for the entire time series

Variable\Animal Cattle Buffaloes Pigs Poultry Horses Sheep GoatsLagoon

Liquid/Slurry 40% Solid storage

Dry lot 46% 41% 54% Pasture range 50% 50% 100% 100% 100% Daily spread 2% 4%

Digester 6% Burned for fuel 2% 5% Pit <1 month Pit >1 month

Poultry manure with litter 100% Other

Emission factors are default values proposed by the 2006 IPCC guidelines in tables 10.21.

Table 57 - N2O emission factors for manure management - kg N2O-N/kg Nex

Lagoon Liquid/Slurry Solid

storage Dry lot

Daily spread

Digester Pit

<1 month Pit

>1 month Poultry manure

0 0.005 0.005 0.02 0 0 0.002 0.002 0.001

Results for N2O (direct emissions)

Table 58 - N2O direct Emissions

Year 1994 2000 2005 2010 2015 2016 N2O (Ggt/year) 2.18 2.32 2.50 2.62 2.22 2.23

3.B – Land

The calculations for the lands are based on a comprehensive monitoring of the land use and a country specific estimate for each type of land.

Activity data

The activity data is the set of land use matrixes implemented thanks to the comparison of different cartographies for 2006, 2010 and 2014. These matrixes are mostly focusing on forest areas because they were elaborated in the framework of the REDD+ program to define the forest reference level for Cambodia.

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Table 59 - Activity data – Aggregated area land and land use changes (1 year matrixes) – ha or ha/Year

Year Forest

becoming other land

Other land becoming

forest

Forest remaining

forest

Other land remaining other land

Total forest

Total other land

2000 132733 37780 11363669 6626492 11401449 6759225 2001 132733 37780 11268715 6721446 11306495 6854179 2002 132733 37780 11173762 6816399 11211541 6949132 2003 132733 37780 11078808 6911353 11116587 7044086 2004 132733 37780 10983854 7006307 11021634 7139040 2005 132733 37780 10888901 7101260 10926680 7233994 2006 132733 37780 10793947 7196214 10831727 7328947 2007 132733 37780 10698993 7291168 10736773 7423901 2008 132733 37780 10604039 7386121 10641819 7518855 2009 132733 37780 10509086 7481075 10546865 7613808 2010 579280 95845 10356066 7129482 10451912 7708762 2011 579280 95845 9872632 7612917 9968477 8192197 2012 579280 95845 9389197 8096351 9485043 8675631 2013 579280 95845 8905763 8579786 9001608 9159066 2014 579280 95845 8422328 9063220 8518173 9642501 2015 579280 95845 7938894 9546655 8034739 10125935 2016 579280 95845 7455459 10030089 7551305 10609369

Methodology

For this inventory all the fluxes are calculated by stock variation by implanting the following equation 2.5 of the 2006 IPPC guidelines according to this:

∆𝐶 𝐶 𝐶

𝑡 𝑡

Where: ∆𝐶 = annual carbon stock change in the pool, tonnes C yr-1 Ct1 = carbon stock in the pool at time t1, tonnes C Ct2 = carbon stock in the pool at time t2, tonnes C

The different stocks are estimated based on different scientific references and national expertise. They are estimated for above ground and belowground biomass.

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Table 60 - Parameter – Biomass content of forestlands

Land use/cover Above ground

biomass (t)*

Below ground biomass (t)** Category Sub-category

Forest

Natural forest

Evergreen 163 31 Semi-evergreen 243 44

Deciduous 85 18 Pine forest 100 20 Bamboo 0 0

Mangrove 150 29 Rear mangrove 165 32 Flooded forest 70 15

Forest regrowth 75 16

Planted forest Pine plantation 100 20 Other plantation 100 20

* Above ground biomass is estimated thanks to a various sources (UN-REDD, UNDP, IPCC, etc.) as presented in the Forest Reference Level (FRL) ** Below ground biomass is estimated on the basis of above ground biomass thanks to the equations proposed by Cairns et al (1997) in IPCC (2003)

Results

The emissions of this sub-sector have not been disaggregated into more detailed categories because all lands which are not forests were aggregated in the baseline data used by the inventory. In the current inventory, all GHG estimates are related to forest, they may concern afforestation, deforestation or changes in forests. Nevertheless deforestation, is not supposed to be reported under forest category but under the final use category, which is not known. For this reason, it was preferred to keep only one aggregated value for all land use estimates (category 3.B) in the nomenclature.

Table 61 - Land Emissions

AGB + BGB Fluxes (tC/yr)

2000 2005 2010 2015 2016

Forest becoming other land* -9165575 -9165575 -40230160 -40230160 -40230160

Other land* becoming forest 1933497 1933497 5339125 5339125 5339125

Forest remaining forest -136636 -136636 -839303 -839303 -839303

Other land* remaining other land* 0 0 0 0 0

Total forest 1796860 1796860 4499822 4499822 4499822 Total other land* -9165575 -9165575 -40230160 -40230160 -40230160 Total (tC/yr) -7368715 -7368715 -35730339 -35730339 -35730339

*Other lands encompass all lands which are not forests (croplands, grasslands, etc.)

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Table 62 – CO2 emissions for Land (Gg)

AGB + BGB Fluxes 1994 2000 2005 2010 2015 2016 Emissions (Gg CO2/yr) 34 149 34 149 34 149 151 274 151 274 151 274Removals (Gg CO2/yr) -7 130 -7 130 -7 130 -20 263 -20 263 -20 263 Emissions/Removals (Gg CO2/yr) 27 019 27 019 27 019 131 011 131 011 131 011

3.C.1 - Emissions from biomass burning

Few information is known on biomass burning in Cambodia. For crop residue burning, relevant and accurate data has been found in a scientific publication (San et al, 20097), this publication was used to estimate biomass burning from rice cultivation.

For grassland burning the estimates used in the first and second national communication that 50% (IPCC 1996 guidelines) of grassland was burnt has been kept for the entire time series.

Activity data

The activity data is the area concerned by biomass burning. For crop residues, biomass burning was considered for rice crops and sugar cane cultivation. For rice crops, it was estimated that straw is removed on 100% of rice fields but remaining stubble is burnt in some cases (stubble is supposed to be burnt on 30% in rainfed areas and 20% in irrigated areas). For sugar cane, burning before harvest is very common because harvest is difficult without burning when there is no mechanisation, it was estimated that 100% of the area of sugar cane is burnt. For other crops no information was found, it was supposed that residues are not burnt.

Table 63 - Activity data – Area and biomass burnt

Year Area burnt (ha) Biomass burnt (t)

rice sugar cane grassland rice sugar cane grassland

1990 541 500 6 000 240 000 155 930 39 000 984 000 1991 500 700 6 000 240 000 145 822 39 000 984 000 1992 490 620 6 000 240 000 140 286 39 000 984 000 1993 532 088 6 473 240 000 151 752 42 075 984 000 1994 431 880 7 000 240 000 128 453 45 500 984 000 1995 555 700 7 420 241 417 176 718 48 230 989 808 1996 541 840 7 022 242 833 173 029 45 643 995 617 1997 556 387 8 035 244 250 176 131 52 228 1 001 425 1998 566 190 6 933 245 667 179 917 45 065 1 007 233 1999 600 893 8 374 247 083 197 238 54 431 1 013 042 2000 547 648 7 480 248 500 186 141 48 620 1 018 850 2001 569 278 7 727 248 500 191 737 50 226 1 018 850 2002 572 072 9 395 248 500 186 738 61 068 1 018 850 2003 644 778 8 482 248 500 218 531 55 133 1 018 850 2004 603 372 6 739 248 500 199 442 43 804 1 018 850 2005 692 247 5 992 248 500 252 324 38 948 1 018 850

7 Estimation of methane and nitrous oxide emissions from rice field with rice straw management in Cambodia. Vibol San, Sirintornthep Towprayoon. Article in Environmental Monitoring and Assessment · April 2009

63

Year Area burnt (ha) Biomass burnt (t)

rice sugar cane grassland rice sugar cane grassland

2006 722 156 8 296 248 500 263 714 53 924 1 018 850 2007 735 650 10 458 248 500 275 179 67 977 1 018 850 2008 747 946 13 297 248 500 286 103 86 431 1 018 850 2009 763 976 13 533 248 500 296 915 87 965 1 018 850 2010 798 126 17 072 248 500 317 423 110 968 1 018 850 2011 806 122 22 069 248 500 331 674 143 449 1 018 850 2012 787 528 27 859 248 500 321 047 181 084 1 018 850 2013 842 346 30 665 248 500 345 973 199 323 1 018 850 2014 859 565 25 503 248 500 187 061 165 770 1 018 850 2015 858 744 27 316 248 500 348 218 177 554 1 018 850 2016 878 079 28 972 248 500 191 052 188 318 1 018 850

Methodology

Estimation of greenhouse gas emissions from fire were calculated according to the following equation:

𝐿 𝐴 ∗ 𝑀 ∗ 𝐶 ∗ 𝐺 ∗ 10

Where:

Lfire = amount of greenhouse gas emissions from fire, tonnes of each GHG e.g., CH4, N2O, etc. A = area burnt, ha MB = mass of fuel available for combustion, tonnes ha-1. This includes biomass, ground litter and dead wood. When Tier 1 methods are used the litter and dead wood pools are assumed zero, except where there is a land-use change. Cf = combustion factor, dimensionless Gef = emissions factor, g kg-1 dry matter burnt Note: Where data for MB and Cf are not available, a default value for the amount of fuel actually burnt (the product of MB and Cf) can be used from IPCC guidelines.

Emission factors are default values proposed by the IPCC 2006 guidelines in table 2.5.

Table 64 - CH4 and N2O emission factors for biomass burning

Variable CH4 N2O Agricultural residues (g/kg) 2.7 0.07 Grassland (g/kg) 2.3 0.21

Results

Table 65 - CH4 emissions for biomass burning (Gg)

CH4 (Gg/yr) 1994 2000 2005 2010 2015 2016 Crop residue burning 0.47 0.63 0.79 1.16 1.42 1.02 Grassland burning 2.26 2.34 2.34 2.34 2.34 2.34

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Table 66 - NO2 emissions for biomass burning (Gg)

N2O (Gg/yr) 1994 2000 2005 2010 2015 2016 Crop residue burning 0.01 0.02 0.02 0.03 0.04 0.03 Grassland burning 0.21 0.21 0.21 0.21 0.21 0.21

3.C.2 – Liming

No data on liming were collected, CO2 emissions from liming are thus neglected. This activity is supposed to be weak in Cambodia.

3.C.3 - Urea application Activity data

The activity data is the amount of urea spread in the fields. Data on fertilizers are not easy to use and data treatment was necessary to estimate a relevant estimate of fertilizer use in Cambodia. For this source only urea must be considered among fertilizer (mostly included in urea and urea ammonium nitrate). The form of nitrogen fertilizer is provided by FAOSTAT (even if this data is very fluctuating on the period). Gaps in the data sets are fulfilled by extrapolation. Table 67 - Activity data – Urea application (Gg)

Year Urea (t) Urea ammonium nitrate (t) Source 1990 600 0 FAOSTAT 1991 1 500 0 FAOSTAT 1992 1 200 0 FAOSTAT 1993 3 600 0 FAOSTAT 1994 2 200 0 FAOSTAT 1995 2 200 0 FAOSTAT 1996 1 600 0 FAOSTAT 1997 2 000 0 FAOSTAT 1998 3 220 0 FAOSTAT 1999 2 244 0 estimate 2000 2 244 0 estimate 2001 2 244 0 estimate 2002 2 244 0 estimate 2003 2 244 0 estimate 2004 2 244 0 estimate 2005 2 244 0 estimate 2006 2 244 0 estimate 2007 2 559 0 FAOSTAT 2008 13 377 483 FAOSTAT 2009 16 129 1 476 FAOSTAT 2010 40 629 294 FAOSTAT 2011 23 378 751 estimate 2012 23 378 751 estimate 2013 23 378 751 estimate

65

2014 23 378 751 estimate 2015 23 378 751 estimate 2016 23 378 751 estimate

Methodology and emission factors

CO2 emissions from urea application are estimated with the tier 1 methodology from the 2006 IPCC guidelines. The emission factor is 0.2 tC/t urea. The fertilizer named “Urea ammonium nitrate” (UAN) contains approximatively 50% of urea, the emission factor is thus 0.1 tC/t UAN.

𝐶𝑂 𝐶 𝐸𝑚𝑖𝑠𝑠𝑖𝑜𝑛 𝑀 ∗ 𝐸𝐹 Where: CO2-C Emission = annual C emissions from urea application, tonnes C yr-1 M = annual amount of urea fertilization, tonnes urea yr-1 EF = emission factor, tonne of C (tonne of urea)-1

Results

Table 68 - CO2 emissions for Urea application

Gas 1994 2000 2005 2010 2015 2016 CO2 (Gg) 1.61 1.65 1.65 29.90 17.42 17.42

3.C.4 - Direct N2O emissions from managed soils Activity data

Direct N2O emissions are based on different nitrogen inputs. Mineral fertilizers, organic fertilisers, pasture and crop residues are taken into account for this calculation.

Mineral fertilisation is not easy to estimate in Cambodia. Data by nutrients and products are provided by FAOSTAT for some years and the Ministry of Commerce (MoC) provides statistics on total fertilisers (tons of product) since 2002. FAOSTAT data by nutrient and data from MoC are rather consistent considering average nutrient contents of fertilizers (20% of N in nitrogenous fertilizers, 30% of P2O5 in phosphate fertilizers and 20% of K2O in potash fertilizers). The trend of fertiliser consumption is similar in both FAOSTAT data and MoC. For the inventory it was chosen to use MoC data to estimate the fertilizer consumption associated with nitrogen content of fertilizer indicated by FAOSTAT data. This mineral fertilisation, which remains rather low, is supposed applied on rice cultivation (assumption due to missing additional elements on the type of crop fertilised with mineral fertiliser).

Organic fertilisation is directly estimated from the livestock calculation. All organic calculation is also considered in rice cultivation.

Nitrogen inputs due to pasture are directly estimated from livestock calculations. All nitrogen inputs from pasture are put on other fields than rice areas.

Nitrogen inputs due to crop residues are calculated on the basis of crop areas and crop productions. Crop residues were estimated for rice, maize, castor oil,

66

cotton, sesame, beans, peanuts soybeans, cassava, sweet potatoes and other roots and tubers.

Table 69 - Activity data – Inorganic fertilizers

Year Inorganic fertilizer (tons of product)

Nitrogen Content (%) Nitrogen in fertilizers (tN)

1990 7 044 1991 7 044 1992 7 044 1993 7 044 1994 7 044 1995 7 044 1996 7 044 1997 7 044 1998 7 044 1999 7 044 2000 7 044 2001 7 044 2002 78 393 9% 7 044 2003 78 920 9% 7 117 2004 79 511 9% 7 438 2005 114 278 9% 10 441 2006 112 404 9% 10 175 2007 111 525 7% 7 572 2008 127 450 11% 13 608 2009 186 931 11% 20 485 2010 196 123 11% 21 672 2011 259 051 13% 32 668 2012 335 863 14% 47 056 2013 364 317 16% 57 347 2014 399 764 17% 67 319 2015 446 344 18% 78 849 2016 393 005 17% 68 505

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Table 70 - Activity data – Nitrogen inputs (tN)

Year

Urine and dung

deposited by cattle, poultry

and pigs (t N)

Urine and dung

deposited by sheep

and others (t N)

Inorganic fertilizers (t

N)

Organic fertilizer

applied to soils (t N)

Rice residues (t

N)

Other Crop residues (t

N)

1990 43171 17 008 7 044 40 952 16 401 2 828 1991 44677 17 437 7 044 42 349 15 447 2 876 1992 48851 18 517 7 044 47 146 14 756 3 164 1993 50316 18 955 7 044 48 694 15 905 2 650 1994 51878 18 633 7 044 48 950 13 842 2 727 1995 55141 17 648 7 044 50 377 19 549 2 917 1996 54667 17 184 7 044 50 528 19 202 3 158 1997 55834 16 069 7 044 51 632 19 476 3 339 1998 53046 16 069 7 044 49 985 19 921 2 783 1999 54818 15 187 7 044 50 163 22 057 4 071 2000 59237 16 069 7 044 52 960 21 161 4 265 2001 56785 14 568 7 044 51 237 21 753 4 546 2002 57887 14 566 7 044 52 236 21 009 4 776 2003 59091 15 330 7 117 53 776 24 835 7 755 2004 60172 16 435 7 438 54 576 22 597 8 606 2005 63205 15 691 10 441 57 273 29 447 10 206 2006 66206 16 750 10 175 59 780 30 764 13 637 2007 66675 17 825 7 572 59 786 32 381 15 810 2008 68580 17 325 13 608 60 320 33 934 18 970 2009 70485 16 825 20 485 60 854 35 449 21 763 2010 68972 16 244 21 672 60 536 37 898 23 336 2011 67437 15 989 32 668 59 821 39 380 29 709 2012 66701 15 242 47 056 59 725 42 160 30 894 2013 67911 14 218 57 347 61 906 42 232 30 607 2014 60442 12 637 67 319 55 820 17 518 28 481 2015 57470 11 859 78 849 53 920 42 346 28 724 2016 57346 12 183 68 505 54 563 17 924 32 371

Methodology and emission factors

N2O emissions from nitrogen inputs are estimated with the tier 1 methodology from the 2006 IPCC guidelines.

𝑁 𝑂 𝑁 𝑁 𝑂 𝑁 𝑁 𝑂 𝑁 𝑁 𝑂 𝑁

Where

𝑁 𝑂 𝑁 𝐹 𝐹 𝐹 𝐹 ∗ 𝐸𝐹 𝐹 𝐹 𝐹 𝐹 ∗ 𝐸𝐹

68

𝑁 𝑂 𝑁 𝐹 , , ∗ 𝐸𝐹 , 𝐹 , , ∗ 𝐸𝐹 ,

𝐹 , , , ∗ 𝐸𝐹 , , 𝐹 , , , ∗ 𝐸𝐹 , ,

𝐹 , , ∗ 𝐸𝐹 ,

𝑁 𝑂 𝑁 𝐹 , ∗ 𝐸𝐹 , 𝐹 , ∗ 𝐸𝐹 , Where: N2ODirect –N = annual direct N2O–N emissions produced from managed soils, kg N2O–N yr-1 N2O–NN inputs = annual direct N2O–N emissions from N inputs to managed soils, kg N2O–N yr-1 N2O–NOS = annual direct N2O–N emissions from managed organic soils, kg N2O–N yr-1 N2O–NPRP = annual direct N2O–N emissions from urine and dung inputs to grazed soils, kg N2O–N yr-1 FSN = annual amount of synthetic fertiliser N applied to soils, kg N yr-1 FON = annual amount of animal manure, compost, sewage sludge and other organic N additions applied to soils (Note: If including sewage sludge, cross-check with Waste Sector to ensure there is no double counting of N2O emissions from the N in sewage sludge), kg N yr-1

FCR = annual amount of N in crop residues (above-ground and below-ground), including N-fixing crops, and from forage/pasture renewal, returned to soils, kg N yr-1 FSOM = annual amount of N in mineral soils that is mineralised, in association with loss of soil C from soil organic matter as a result of changes to land use or management, kg N yr-1 FOS = annual area of managed/drained organic soils, ha (Note: the subscripts CG, F, Temp, Trop, NR and NP refer to Cropland and Grassland, Forest Land, Temperate, Tropical, Nutrient Rich, and Nutrient Poor, respectively) FPRP = annual amount of urine and dung N deposited by grazing animals on pasture, range and paddock, kg N yr-1 (Note: the subscripts CPP and SO refer to Cattle, Poultry and Pigs, and Sheep and Other animals, respectively) EF1 = emission factor for N2O emissions from N inputs, kg N2O–N (kg N input)-1(Table 11.1) EF1FR is the emission factor for N2O emissions from N inputs to flooded rice, kg N2O–N (kg N input)-1 (Table 11.1) 5 EF2 = emission factor for N2O emissions from drained/managed organic soils, kg N2O–N ha-1 yr-1; (Table 11.1) (Note: the subscripts CG, F, Temp, Trop, NR and NP refer to Cropland and Grassland, Forest Land, Temperate, Tropical, Nutrient Rich, and Nutrient Poor, respectively) EF3PRP = emission factor for N2O emissions from urine and dung N deposited on pasture, range and paddock by grazing animals, kg N2O–N (kg N input)-1; (Table 11.1) (Note: the subscripts CPP and SO refer to Cattle, Poultry and Pigs, and Sheep and Other animals, respectively)

Emission factors are default values proposed by the IPCC 2006 guidelines in tables 11.1.

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Table 71 - N2O emission factors for managed soils

Inorganic fertilizers

Organic fertilzer applied to soils

Urine and dung

deposited by cattle,

poultry and pigs

Urine and dung

deposited by sheep and

others

Crop residu

es

EF for flooded

rice fields

Emission Factor (Kg N2O-N /(kg N)

0.01 0.01 0.02 0.01 0.01 0.003

Results

Table 72 - N2O emissions for managed soils

1994 2000 2005 2010 2015 2016 N2O (kt) 2.30 2.56 2.85 3.36 3.27 3.17

3.C.5 - Indirect N2O emissions from managed soils Activity data

Indirect N2O emissions are due to volatilization and to leaching of nitrogen. These activities are calculated on the basis of the data available in the estimation direct N2O emissions and specific parameters provide by the IPCC 2006 guidelines.

Table 73 - Activity data – Volatilized and leached nitrogen on managed soils

Year Volatilized N from

agricultural inputs of N (tN) N that is lost through leaching

and run-off (tN) 1990 20 931 38 222 1991 21 597 38 949 1992 23 607 41 844 1993 24 297 43 069 1994 24 597 42 922 1995 25 337 45 802 1996 25 180 45 535 1997 25 412 46 018 1998 24 524 44 654 1999 24 738 46 002 2000 26 358 48 221 2001 25 222 46 780 2002 25 642 47 256 2003 26 351 50 371 2004 26 980 50 947 2005 28 278 55 879 2006 29 565 59 193 2007 29 614 60 014 2008 30 606 63 821 2009 31 681 67 758 2010 31 317 68 597

70

2011 31 916 73 501 2012 33 039 78 533 2013 34 542 82 266 2014 32 512 72 665 2015 32 535 81 950 2016 31 669 72 868

Methodology and emission factors

The N2O emissions from atmospheric deposition of N volatilised from managed soil are estimated using the equation 11.9 from IPCC guidelines:

𝑁 𝑂 𝑁 𝐹 ∗ 𝐹𝑟𝑎𝑐 𝐹 𝐹 ∗ 𝐹𝑟𝑎𝑐 ∗ 𝐸𝐹

Where N2O(ATD)–N = annual amount of N2O–N produced from atmospheric deposition of N volatilised from managed soils, kg N2O–N yr-1 FSN = annual amount of synthetic fertiliser N applied to soils, kg N yr-1 FracGASF = fraction of synthetic fertiliser N that volatilises as NH3 and NOx, kg N volatilised (kg of N applied)-1 (Table 11.3) FON = annual amount of managed animal manure, compost, sewage sludge and other organic N additions applied to soils, kg N yr-1 FPRP = annual amount of urine and dung N deposited by grazing animals on pasture, range and paddock, kg N yr-1 FracGASM = fraction of applied organic N fertiliser materials (FON) and of urine and dung N deposited by grazing animals (FPRP) that volatilises as NH3 and NOx, kg N volatilised (kg of N applied or deposited)-1 (Table 11.3) EF4 = emission factor for N2O emissions from atmospheric deposition of N on soils and water surfaces, [kg N–N2O (kg NH3–N + NOx–N volatilised)-1] (Table 11.3)

Conversion of N2O(ATD)-N emissions to N2O emissions for reporting purposes is performed by using the following equation:

𝑁 𝑂 𝑁 𝑂 𝑁 ∗ 44/28

The N2O emissions from leaching and runoff in regions where leaching and runoff occurs are estimated using Equation 11.10 from IPCC guidelines:

𝑁 𝑂 𝑁 𝐹 𝐹 𝐹 𝐹 𝐹 ∗ 𝐹𝑟𝑎𝑐 ∗ 𝐸𝐹

Where N2O(L)–N = annual amount of N2O–N produced from leaching and runoff of N additions to managed soils in regions where leaching/runoff occurs, kg N2O–N yr-1

71

FSN = annual amount of synthetic fertiliser N applied to soils in regions where leaching/runoff occurs, kg N yr-1 FON = annual amount of managed animal manure, compost, sewage sludge and other organic N additions applied to soils in regions where leaching/runoff occurs, kg N yr-1 FPRP = annual amount of urine and dung N deposited by grazing animals in regions where leaching/runoff occurs, kg N yr-1 FCR = amount of N in crop residues (above- and below-ground), including N-fixing crops, and from forage/pasture renewal, returned to soils annually in regions where leaching/runoff occurs, kg N yr-1 FSOM = annual amount of N mineralised in mineral soils associated with loss of soil C from soil organic matter as a result of changes to land use or management in regions where leaching/runoff occurs, kg N yr-1 (from Equation 11.8) FracLEACH-(H) = fraction of all N added to/mineralised in managed soils in regions where leaching/runoff occurs that is lost through leaching and runoff, kg N (kg of N additions)-1 (Table 11.3) EF5 = emission factor for N2O emissions from N leaching and runoff, kg N–N2O (kg N leached and runoff)-

1] (Table 11.3)

Conversion of N2O(ATD)-N emissions to N2O emissions for reporting purposes is performed by using the following equation:

𝑁 𝑂 𝑁 𝑂 𝑁 ∗ 44/28

Parameters and emission factors are default values proposed by the IPCC 2006 guidelines in tables 11.3.

Table 74 - Parameters and emission factors for indirect emissions for managed soils

Parameters and emission factors Value Frac leach (kg N/kg of N additions) 0.3 Frac gasm (kg N volatilized/kg of N applied or deposited) for organic fertilizer 0.2 Frac gasf (kg N volatilized/kg of N applied) for synthetic fertilizer 0.1 Atmospheric deposition (kg N2O-N/kg NH3-N+NOx-N volatilized) 0.01 Nitrogen Leaching and runoff (kg N2O-N/kg N leaching/runoff) 0.0075

Results

Table 75 - N2O indirect emission for managed soils

N2O (kt/yr) 1994 2000 2005 2010 2015 2016 Atmospheric deposition (kt/yr) 0.390 0.427 0.464 0.492 0.453 0.460 Nitrogen Leaching and runoff (kt/yr) 0.094 0.102 0.109 0.118 0.104 0.106 Totals (kt/yr) 0.483 0.529 0.573 0.609 0.557 0.566

3.C.6 - Indirect N2O emissions from manure management Activity data On the same basis as nitrogen in managed soils, indirect N2O emissions may occur during storage of manure management. The methodologies are similar and based on IPCC 2006 guidance. The percentages of losses due to volatilization are based on default values provide

72

in Table 10.22 of the IPCC 2006 guidelines and the rates of leaching are obtained by difference between the total losses presented in Table 10. 23 and the losses by volatilization. Table 76 - Activity data – Volatilized and leached nitrogen from manure management

Year N volatilized (tN/year) N leached (tN/year)

1990 20 645 6 686 1991 21 377 6 920 1992 23 938 7 645 1993 24 771 7 898 1994 24 802 7 953 1995 25 509 8 189 1996 25 745 8 206 1997 26 458 8 343 1998 25 720 8 093 1999 25 786 8 153 2000 27 173 8 686 2001 26 438 8 362 2002 27 036 8 544 2003 27 781 8 761 2004 27 934 8 848 2005 29 514 9 270 2006 30 722 9 683 2007 30 636 9 756 2008 30 878 9 872 2009 31 120 9 989 2010 31 298 9 982 2011 31 042 9 861 2012 31 180 9 837 2013 32 717 10 196 2014 29 634 9 173 2015 28 826 8 863 2016 29 283 8 984

73

Methodology and emission factors

The methodology and emission factors are similar to those used on managed soils.

Results

Table 77 - N2O indirect emission for manure management

N2O (Gg/yr) 1994 2000 2005 2010 2015 2016 Atmospheric deposition 0.390 0.427 0.464 0.492 0.453 0.460 Nitrogen Leaching and runoff 0.094 0.102 0.109 0.118 0.104 0.106 Totals 0.483 0.529 0.573 0.609 0.557 0.566

3.C.7 - Rice cultivation

Activity data

The areas of rice cultivation are estimated on the basis of different datasets. MAFF publications were used for the period since 2004, with the detail for both wet and dry seasons (MAFF Annual Report 2016-2017 and direction for 2017-2018, and MAFF annual report 2013-2014). For the years before 2004, total harvested area was based on FAOSTAT and the split between wet and dry season was estimated thanks to different sources (national communications, etc.). Production is also available but is only indirectly used to estimate CH4 from rice cultivation in the tier 1 methodology (production is used to estimate the amount of residues). For this inventory, the 2006 IPCC guidelines were implemented, and 6 types of rice cultivation were defined in relation with IPCC requirements.

Rice Cultivation

4: Lowland rainfed area

3: Lowland irrigated area(1 harvest /yr)

Cultivationduring wet season

Cultivationduring dry season

2: Lowland irrigated area(2 harvests/yr)

1: Lowland Irrigated area(2 harvests/yr)

5: Upland 6: Deep water

74

Type 1 (dry season - lowland irrigated area - 2 harvests/yr): The area is estimated on the basis of the area harvested in dry season (MAFF statistics since 2004 and for the following years 1993, 1994, 1995, 2000) Type 2 (wet season - lowland irrigated area - 2 harvests/yr): the area is the same as type 1. It is estimated on the basis of rice area harvested during dry season because it is considered that these areas are also irrigated (when necessary) during the wet season. Type 3 (wet season - lowland irrigated area - 1 harvest/yr): Cambodia made developed a lot its irrigation during the covered period. It is estimated by the International Rice Research Institute (IRRI) that irrigated area was around 15% in 2005 and 25% in 20108 in Cambodia. 25% of rice area represents more than the area harvested in dry season which means that some areas are irrigated to produce rice only in wet season. The area of type 3 is estimated by difference between total irrigated area and the irrigated areas which allows 2 harvests/yr (types 1 and 2). Type 4 (wet season - lowland rainfed area): this area is obtained by difference between total harvested area and all other types of rice cultivation. Type 5 (wet season - upland area): this area (35 000 ha) is estimated on the basis of the area estimated in 1993 (MAFF) and maintained for the entire times series. Type 6 (wet season - deep water): this area (108 500 ha) is estimated on the basis of the area estimated in 1993 (Bulletin of agriculture statistics, 1993) and maintained for the entire times series.

8 GRiSP (Global Rice Science Partnership). 2013. Rice almanac, 4th edition. Los Baños Philippines): International Rice Research Institute. 283 p.

Rice Cultivation

4: Lowland rainfed area

3: Lowland irrigated area(1 harvest /yr)

Cultivationduring wet season

Cultivationduring dry season

2: Lowland irrigated area(2 harvests/yr)

1: Lowland Irrigated area(2 harvests/yr)

5: Upland 6: Deep water

75

Table 78 - Activity data – Area of rice crops split into 6 types (1000 ha/yr)

Year

Type 1 (dry season - lowland irrigated area - 2

harvests/yr)

Type 2 (wet season - lowland irrigated area - 2

harvests/yr)

Type 3 (wet

season - lowland irrigated area - 1

harvest/yr)

Type 4 (wet

season - lowland rainfed area)

Type 5 (wet

season -

upland area)

Type 6 (wet

season - deep water)

Total harvested

area

1990 150 150 0 1 412 35 109 1 855 1991 150 150 0 1 276 35 109 1 719 1992 150 150 0 1 242 35 109 1 685 1993 150 150 0 1 380 35 109 1 824 1994 165 165 0 1 021 35 109 1 495 1995 215 215 0 1 351 35 109 1 924 1996 219 219 0 1 298 35 109 1 879 1997 222 222 0 1 341 35 109 1 929 1998 226 226 0 1 367 35 109 1 963 1999 229 229 0 1 477 35 109 2 079 2000 233 233 0 1 294 35 109 1 903 2001 248 248 0 1 341 35 109 1 980 2002 263 263 0 1 325 35 109 1 995 2003 278 278 0 1 542 35 109 2 242 2004 293 293 0 1 379 35 109 2 109 2005 321 321 0 1 629 35 109 2 414 2006 328 328 44 1 673 35 109 2 516 2007 344 344 78 1 657 35 109 2 567 2008 361 361 112 1 636 35 109 2 613 2009 384 384 143 1 620 35 109 2 675 2010 405 405 193 1 631 35 109 2 777 2011 472 472 121 1 558 35 109 2 767 2012 495 495 78 1 768 35 109 2 980 2013 483 483 138 1 721 35 109 2 969 2014 491 491 144 1 760 35 109 3 029 2015 489 489 145 1 759 35 109 3 026 2016 519 519 127 1 792 35 109 3 100

76

Methodology and emission factors

CH4 emissions from rice cultivation are estimated with the tier 1 methodology from the 2006 IPCC guidelines. Equations for rice cultivation is equation 5.1:

𝐶𝐻4𝑅𝑖𝑐𝑒 𝐸𝐹 , , ∗ 𝑡 , , ∗ 𝐴 , , ∗ 10, ,

Where: CH4 Rice = annual methane emissions from rice cultivation, Gg CH4 yr-1 EFijk = a daily emission factor for i, j, and k conditions, kg CH4 ha-1 day-1 tijk = cultivation period of rice for i, j, and k conditions, day Aijk = annual harvested area of rice for i, j, and k conditions, ha yr-1 i, j, and k = represent different ecosystems, water regimes, type and amount of organic amendments, and other conditions under which CH4 emissions from rice may vary

Emissions factors are based on the equations 5.2 and 5.3 and different assumptions relative to rice management. The 6 types of rice cultivation defined previously were subdivided into 4 subcategories dependent on residue management and manure application. This subdivision was made on the basis of a scientific publication (San et al, 20099).

Subcategory A: Manure application and stubble incorporation Subcategory B: Manure application and stubble burning Subcategory C: No manure application and stubble incorporation Subcategory D: No manure application and stubble burning

Table 79 - Rice cultivation subdivision

Variable Wet season Dry season A: Manure + Stubble incorporation 53% 48% B: Manure + Stubble burning 23% 12% C: No manure + Stubble incorporation 18% 32% D: No manure + Stubble burning 8% 8%

These values are estimated for the years 2005-2006 but applied for the entire time series.

The amount of manure and stubble incorporated are calculated consistently with the rest of the GHG inventory for livestock and crop residues.

9 Estimation of methane and nitrous oxide emissions from rice field with rice straw management in Cambodia. Vibol San, Sirintornthep Towprayoon. Article in Environmental Monitoring and Assessment · April 2009

77

Parameters and emission factor - kg CH4/ha/day

𝐸𝐹 𝐸𝐹 ∗ 𝑆𝐹 ∗ 𝑆𝐹 ∗ 𝑆𝐹 ∗ 𝑆𝐹 , Where: EFi = adjusted daily emission factor for a particular harvested area EFc = baseline emission factor for continuously flooded fields without organic amendments SFw = scaling factor to account for the differences in water regime during the cultivation period (from Table 5.12) SFp = scaling factor to account for the differences in water regime in the pre-season before the cultivation period (from Table 5.13) SFo = scaling factor should vary for both type and amount of organic amendment applied (from Equation 5.3 and Table 5.14) SFs,r = scaling factor for soil type, rice cultivar, etc., if available

𝑆𝐹 1 𝑅𝑂𝐴 ∗ 𝐶𝐹𝑂𝐴

.

Where: SFo = scaling factor for both type and amount of organic amendment applied ROAi = application rate of organic amendment i, in dry weight for straw and fresh weight for others, tonne ha-1 CFOAi = conversion factor for organic amendment i (in terms of its relative effect with respect to straw applied shortly before cultivation) as shown in Table 5.14.

Considering the types (1 to 6) and the subdivision (A, B, C, D), 24 categories were defined with specific emission factors. Emission factors are changing on the time series because of changes in crop residues and manure availability.

Considering the expert judgements used for the first national communication cultivation length is fixed at 115 days for the dry season and 165 days for the wet season. This value could be improved by taking into account the changes in rice varieties which lead to shorter cultivation periods.

Table 80 - Rice cultivation emission factors

kg CH4/ha/yr 1994 2000 2005 2010 2015 2016

Type 1A 307 297 288 284 275 275 Type 1B 256 245 235 230 220 220 Type 1C 233 233 233 233 233 233 Type 1D 214 214 214 214 214 214 Type 2A 440 425 413 407 395 394 Type 2B 368 351 337 330 316 316 Type 2C 335 335 335 335 335 335 Type 2D 307 307 307 307 307 307 Type 3A 255 244 235 230 221 220 Type 3B 250 239 229 224 215 215 Type 3C 172 172 172 172 172 172 Type 3D 166 166 166 166 166 166 Type 4A 71 68 66 64 62 62 Type 4B 70 67 64 63 60 60

78

kg CH4/ha/yr 1994 2000 2005 2010 2015 2016

Type 4C 48 48 48 48 48 48 Type 4D 46 46 46 46 46 46 Type 5A 0 0 0 0 0 0 Type 5B 0 0 0 0 0 0 Type 5C 0 0 0 0 0 0 Type 5D 0 0 0 0 0 0 Type 6A 79 76 73 71 68 68 Type 6B 78 74 71 70 67 67 Type 6C 53 53 53 53 53 53 Type 6D 51 51 51 51 51 51

Results

Table 81 - CH4 emissions from rice cultivation

1994 2000 2005 2010 2015 2016 CH4 (kt/yr) 184 240 309 399 438 453

3.D.1 - Harvested wood products

This category is currently included in the GHG estimate due to limited data and time constrain.

3.5.4. AFOLU emissions trends

Table 82 - Trend of emissions (GHG, Gg CO2-eq)

Inventory Sector 1994 2000 2005 2010 2015 2016

3A. Livestock 5 370.57 5 678.87 6 100.43 6 399.75 5 362.78 5 384.54 3B. Land 27 019 27 019 27 019 131 011 131 011 131 011 3C. Crop cultivation 5 832.01 7 353.45 9 235.95 11 736.33 12 705.57 13 013.13Total 38 221.2 40 050.9 42 355.0 149 147.3 149 079.6 149 408.9

Table 83 - Emissions by gas (Gg)

Inventory Sector

1994 2000 2005 2010 2015 2016

CO2 27 020.23 27 020.26 27 020.26 131 041.14 131 028.66 131 028.66 CH4 375.69 442.23 526.79 627.28 629.41 645.15 N2O 6.07 6.63 7.27 8.13 7.77 7.56

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3.6. Waste sector

3.6.1. Characterization of the sector

The waste sector includes the emissions that occur in the generation and management of waste. Based on the 2006 IPCC Guidelines, the emissions of the waste sector are split in the following categories:

4A. Solid Waste Disposal 4B. Biological treatment of solid waste 4C. Incineration and open burning of waste 4D. Wastewater treatment and discharge

Typically, the most important sources of emissions in this sector are the CH4 emissions from solid waste disposal, CH4 emissions from wastewater treatment and discharge and CO2 emissions which occur in Incineration and open burning of waste.

This edition of the inventory includes estimates for all the categories defined by 2006 IPCC Guidelines.

The following table provides a summary of the emissions reported in the waste sector. Complete reporting tables are provided in section Reporting tables.

Table 84 - Sectoral reporting table – Waste sector – Emissions of year 2016

GREENHOUSE GAS SOURCE AND SINK CATEGORIES

CO2(1) CH4 N2O NOx CO NMVOC SO2

(Gg)

Total waste 994.26 129.1 0.82 NE NE NE NE A. Solid waste disposal NA 57.09 NA NA NA 1. Managed waste disposal sites NA IE 2. Unmanaged waste disposal sites NA IE 3. Uncategorized waste disposal sites NA IE B. Biological treatment of solid waste 0.33 0.02 NA NA NA 1. Composting 0.32 0.02 2. Anaerobic digestion at biogas facilities 0.01 NA C. Incineration and open burning of waste 994.26 9.46 0.14 NA NA NA NA 1. Waste incineration NE NA NE 2. Open burning of waste 994.26 9.46 0.14 D. Wastewater treatment and discharge 61.54 0.66 NA NA NA 1. Domestic wastewater 61.54 0.66 2. Industrial wastewater NA NA 3. Other (as specified in table 5.D) NO NO NO NO NO E. Other (please specify) NO NO NO NO NO NO NO Memo item:(2) Long-term storage of C in waste disposal sites 2,978 Annual change in total long-term C storage 106.01 Annual change in total long-term C storage in HWP waste(3) 29.58

80

3.6.2. Data sources

The following is the list of data sources used for calculating the GHG emissions of the waste sector:

The study “State of Waste Management in Phnom Penh, Cambodia” carried out by UNEP in 2018. This study is available at https://www.researchgate.net/publication/326293569_State_of_Waste_Management_in_Phnom_Penh_Cambodia

Population data from National Committee for Sub-National Democratic Development (NCDD) complemented with the world bank data base

Gross Domestic Product (GDP) from the Ministry of Planning (MOP) complemented with the world bank database

Waste generation from the Ministry of Environment (Based on 2006 IPCC default value)3d

Amount of dung used for producing biogas: energy balance and “Assessment of the Cambodian National Biodigester Program”10

Protein consumption from FAO Percentage of people open burning waste from Yut S. and Seng B., 2018. KAP

on waste management (data of 2012)

3.6.3. Waste emissions by category

The data available at national level on waste generation and management has been used to derive a complete characterization of the overall management of waste in the country and its temporal evolution. Analogously, the data available was used to characterize the typology of wastewater discharges needed for estimating the GHG emissions of the wastewater sector. The following tables show the evolution of the country profile regarding waste generation and management as well as wastewater discharges typology.

10 https://www.sciencedirect.com/science/article/pii/S0973082618302588#bb0185

81

Table 85 – Waste management practices in Cambodia – 1990 - 2016

Year

Total MSW generated

(Gg)

% of waste burned

% of waste composte

d

% of waste used as

animal food

% of waste

recycled

% wastes going to landfills

Columns in grey are not summed. These figures are the breakdown of the % of wastes going to landfill

Total % of

waste going to managed landfills

% of waste going to un-

managed landfills

% of waste to

unmanaged landfills - shallow

% of waste to

unmanaged landfills -

deep

% of waste going to

Unspecified landfills

Before 1990 … 66% 2% 0.302% 0.000% 32% 0% 11% 11% 0% 21% 100%

1990 2 508 66% 2% 0.302% 0.000% 32% 2% 11% 11% 0% 19% 100%1991 2 596 65% 2% 0.300% 0.000% 33% 2% 11% 11% 0% 19% 100%1992 2 689 65% 2% 0.299% 0.000% 33% 2% 11% 11% 0% 20% 100%1993 2 786 65% 2% 0.298% 0.000% 33% 2% 11% 11% 0% 20% 100%1994 2 883 64% 2% 0.297% 0.000% 34% 2% 11% 11% 0% 20% 100%1995 2 977 64% 2% 0.295% 0.000% 34% 2% 11% 11% 0% 21% 100%1996 3 069 64% 2% 0.294% 0.000% 34% 2% 11% 11% 0% 21% 100%1997 3 157 63% 2% 0.293% 0.000% 35% 2% 11% 11% 0% 21% 100%1998 3 241 63% 2% 0.292% 0.000% 35% 2% 11% 11% 0% 22% 100%1999 3 321 62% 2% 0.291% 0.000% 35% 2% 11% 11% 0% 22% 100%2000 3 396 62% 2% 0.291% 0.000% 36% 2% 11% 11% 0% 22% 100%2001 3 550 62% 2% 0.290% 0.000% 36% 2% 11% 11% 0% 23% 100%2002 3 638 61% 2% 0.290% 0.000% 37% 3% 11% 11% 0% 22% 100%2003 3 726 61% 2% 0.290% 0.000% 37% 5% 11% 11% 0% 20% 100%2004 3 661 61% 2% 0.289% 0.000% 37% 9% 11% 11% 0% 17% 100%2005 3 745 60% 2% 0.289% 0.000% 38% 9% 11% 11% 0% 18% 100%2006 3 532 60% 2% 0.288% 0.000% 38% 11% 11% 11% 0% 15% 100%2007 3 601 59% 2% 0.288% 0.000% 38% 13% 12% 12% 0% 13% 100%2008 3 738 59% 2% 0.287% 0.000% 39% 14% 12% 12% 0% 13% 100%2009 3 780 59% 2% 0.287% 0.000% 39% 15% 12% 12% 0% 13% 100%2010 3 847 58% 2% 0.286% 3.197% 36% 15% 12% 12% 0% 10% 100%2011 3 906 58% 2% 0.286% 3.512% 36% 16% 12% 12% 0% 9% 100%2012 3 991 58% 2% 0.285% 1.949% 38% 23% 12% 12% 0% 3% 100%2013 4 086 57% 2% 0.285% 1.824% 39% 24% 12% 12% 0% 3% 100%2014 4 156 57% 2% 0.284% 2.379% 38% 26% 12% 12% 0% 0.3% 100%2015 4 179 57% 2% 0.283% 2.379% 38% 28% 10% 10% 0% 0.3% 100%2016 4 239 57% 2% 0.282% 2.379% 38% 30% 7.90% 7.90% 0% 0.3% 100%

Source 2006 IPCC

defaults*population

Estimate based on Yut S. and Seng B., 2018. KAP on waste management MoE

MoE + Yut S. and Seng B., 2018. KAP on

waste management

MoE Estimate based on Yut S. and Seng B., 2018. KAP on waste management

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Table 86 – Wastewater discharges typology – Assumption on the temporal evolution

Degree of utilization of treatment or discharge pathway or method for each income group U=rural U=urban low income

Septic Tank Latrine Other Sewer None Septic Tank Latrine Other Sewer None Default IPCC for the region 0% 47% 0% 10% 43% 14% 10% 3% 53% 20%

1990 0% 9% 0% 2% 89% 14% 10% 3% 53% 20% 1991 0% 10% 0% 2% 87% 14% 10% 3% 53% 20% 1992 0% 12% 0% 2% 86% 14% 10% 3% 53% 20% 1993 0% 13% 0% 3% 84% 14% 10% 3% 53% 20% 1994 0% 14% 0% 3% 83% 14% 10% 3% 53% 20% 1995 0% 16% 0% 3% 81% 14% 10% 3% 53% 20% 1996 0% 17% 0% 4% 79% 14% 10% 3% 53% 20% 1997 0% 18% 0% 4% 78% 14% 10% 3% 53% 20% 1998 0% 20% 0% 4% 76% 14% 10% 3% 53% 20% 1999 0% 21% 0% 4% 74% 14% 10% 3% 53% 20% 2000 0% 22% 0% 5% 73% 14% 10% 3% 53% 20% 2001 0% 24% 0% 5% 71% 14% 10% 3% 53% 20% 2002 0% 25% 0% 5% 70% 14% 10% 3% 53% 20% 2003 0% 26% 0% 6% 68% 14% 10% 3% 53% 20% 2004 0% 28% 0% 6% 66% 14% 10% 3% 53% 20% 2005 0% 29% 0% 6% 65% 14% 10% 3% 53% 20% 2006 0% 30% 0% 6% 63% 14% 10% 3% 53% 20% 2007 0% 32% 0% 7% 62% 14% 10% 3% 53% 20% 2008 0% 33% 0% 7% 60% 14% 10% 3% 53% 20% 2009 0% 34% 0% 7% 58% 14% 10% 3% 53% 20% 2010 0% 36% 0% 8% 57% 14% 10% 3% 53% 20% 2011 0% 37% 0% 8% 55% 14% 10% 3% 53% 20% 2012 0% 38% 0% 8% 53% 14% 10% 3% 53% 20% 2013 0% 40% 0% 8% 52% 14% 10% 3% 53% 20% 2014 0% 41% 0% 9% 50% 14% 10% 3% 53% 20% 2015 0% 44% 0% 9% 49% 14% 10% 3% 53% 20% 2016 0% 44% 0% 9% 47% 14% 10% 3% 53% 20%

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4A. Solid waste disposal

Category 4A Solid waste disposal includes the emissions that occur in the treatment and disposal of municipal, industrial and other solid waste.

Activity data

Table 87 - Activity data MSW production. Data in tonnes

Year Population (M) Total MSW (Gg) GDP (M USD; current prices)

Total Industrial waste (Gg)

1994 11 2 883 2 770 21.03 2000 13 3 396 3 649 27.71 2005 14 3 745 6 293 47.79 2010 14 3 847 11 634 88.35 2011 14 3 906 12 965 98.46 2012 15 3 991 14 054 106.73 2013 15 4 086 15 229 115.65 2014 15 4 156 16 796 127.55 2015 15 4 179 18 078 137.29 2016 16 4 239 19 843 150.70

Waste per capita/year: 270. Source: default IPCC 2006 Waste generation rate: 0.007594366 Gg/M GDP. Source: calculated using data from the MoE MSW: Municipal solid waste GDP: gross domestic product

Methodology and emission factors

The GHG emissions have been calculated using the tier 1 methodology provided by IPCC 2006 using the default values provided by the guidelines complementing it with national specific information. The IPCC methodology for estimating CH4 emissions from Solid Waste Disposal Sites (SWDP) is based on the First Order Decay (FOD) method. This method assumes that the degradable organic component (degradable organic carbon, DOC) in waste decays slowly throughout a few decades, during which CH4 and CO2 are formed.

Table 88 - Waste composition used

Food Garden Paper Wood Textile Nappies Plastics, other inert

55% 0% 10% 2% 2% 0% 30% Source: •The study “State of Waste Management in Phnom Penh, Cambodia” carried out by UNEP in 2018. This study is available at https://www.researchgate.net/publication/326293569_State_of_Waste_Management_in_Phnom_Penh_Cambodia

The parameters used in the estimation are those provided by 2006 IPCC guidelines for Asia-southeast, “Moist and wet tropical” weather. The starting year for the estimation is 1950.

84

The following tables show the key parameters used in the estimation of emissions:

Table 89 - Key parameters used

Parameters Value used

Methane generation rate constant (k) Food waste 0.4 Garden 0.17 Paper 0.07 Wood and Straw 0.035 Textiles 0.07 Disposable nappies 0.17 Sewage sludge 0.4 Industrial waste 0.17

Delay time (months) 6 Fraction of methane (F) in developed gas 0.5Conversion factor c to CH4 1.33

Regarding the Methane correction factor (MCF), for municipal solid waste the MCF value is calculated using the distribution of waste disposal sites types shown in table Waste management practices in Cambodia above. For industrial wastes, the MCF used in the one that corresponds to a 100% of wastes going to uncategorized landfill sites.

Table 90 – Weighted average methane correction factor

Year MSW Industrial

Weighted average MCF for MSW

Weighted average MCF for Industrial Waste

1994 0.66 0.60 2000 0.66 0.60 2010 0.80 0.60 2015 0.93 0.60 2016 0.96 0.60

Results

Table 91 - CH4 emissions from solid waste disposal

Year CH4 (Gg) 1994 24.21 2005 37.622010 45.52 2011 46.45 2012 47.68 2013 50.60 2014 53.31 2015 55.86 2016 57.79

85

Figure 21 - CH4 emissions from solid waste disposal (Gg CH4)

4B. Biological treatment of waste

Category 4B Biological treatment of waste includes the emissions from composting and anaerobic digestion in biogas facilities. Both activities occurred in the country in the inventoried period.

Activity data

Table 92 - Activity data used

Year  Total Annual amount composted (Gg) Total Annual amount treated by biological treatment facilities (Gg) 

1994 51.34 0

2005 68.43 0

2010 70.80 42.16

2011 72.00 54.34

2012 73.71 47.30

2013 75.62 12.56

2014 77.08 18.37

2015 77.69 18.37

2016 79.00 18.37

The total amount of waste composted has been calculated by applying to national total waste generated the percentage of waste composted (see table on Waste management practices in Cambodia above). The total amount of waste treated by biological treatment facilities has been calculated using data from the energy balance on amount of biogas produced and a conversion

0

10

20

30

40

50

60

70

Gg CH4

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rate (m3/kg) calculated using data from the “Assessment of the Cambodian National Biodigester Programme”.

The following tables show the data used for the calculation and the results obtained.

Table 93 - Activity data – Calculation of conversion rate

Variable Type 1 Type 2 Type 3 Type 4 Type 5

Dung requirements (kg/day) 30 50 70 90 125 Estimated gas production (m3/day) 1.2 2 2.8 3.6 5 Conversion rate (m3/kg) 0.04 0.04 0.04 0.04 0.04

Extracted from: https://www.sciencedirect.com/science/article/pii/S0973082618302588#bb0185

Table 94 - Activity data – Calculation of the amount of waste (animal dung) treated

Variable 2010 2011 2012 2013 2014 2015 2016 Amount of biogas produced and consumed from the Energy Balance (tonnes)

2024 2608 2271 603 882 882 882

Density (kg/m3) 1.2 1.2 1.2 1.2 1.2 1.2 1.2m3 1686333 2173675 1892175 502208 734617 734617 734617Dung (Gg) 42.16 54.34 47.30 12.56 18.37 18.37 18.37

Methodology

The tier 1 methodology proposed by 2006 IPCC has been applied using an emission factor of 4 g CH4/kg waste treated and 0.24 g N2O/kg waste treated for calculating the emissions from compost and an emission factor 0.8 g/kg waste treated for calculating the emissions from anaerobic digestion. There is no recovery of methane.

Results

Table 95 – Emissions from biological treatment of wastes (Gg)

Year CH4 emissions from Composting (Gg)

N2O emissions from Composting (Gg)

CH4 emissions from Anaerobic digestion

(Gg)

1994 0.21 0.012 NO 2005 0.27 0.016 NO 2010 0.28 0.017 0.03 2011 0.29 0.017 0.04 2012 0.29 0.018 0.04 2013 0.30 0.018 0.01 2014 0.31 0.018 0.01 2015 0.31 0.019 0.01 2016 0.32 0.019 0.01

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Figure 22 - CH4 emissions from solid waste disposal (Gg CH4)

Figure 23 - N2O emissions from solid waste disposal (Gg N2O)

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

Gg CH4

Composting Anaerobic digestion

0.000

0.002

0.004

0.006

0.008

0.010

0.012

0.014

0.016

0.018

0.020

Gg N2O

Composting

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4C. Incineration and open burning

Category 4C2 Incineration and open burning of waste includes the emissions from the combustion of waste in controlled facilities or in open dumps. Incineration of waste does not occur in Cambodia and therefore it is not included in the inventory.

Activity data

Table 96 - Activity data on open burning

Year Population Burning Waste (%) Total Amount of MSW

Open-burned – wet basis (Gg)

1994 64% 1,113 2005 60% 1,353 2010 58% 1,346 2011 58% 1,357 2012 58% 1,378 2013 57% 1,409 2014 57% 1,431 2015 57% 1,437 2016 57% 1,455

The percentage of population burning waste has been estimated based on the information available in Yut S. and Seng B., 2018. KAP on waste management.

The Activity data has been calculated using the following equation:

𝑀𝑆𝑊 𝑃 ∗ 𝑃 ∗ 𝑀𝑆𝑊 ∗ 𝐵 ∗ 365 ∗ 10

Where:

MSWB = Total amount of municipal solid waste open-burned, Gg/yr P = population (capita) Pfrac = fraction of population burning waste, (fraction) MSWp = per capita waste generation, Kg waste/capita/day Bfrac = fraction of the waste amount that is burned relative to the total amount of waste treated, (fraction) 365 = number of days by year 10-6 = conversion factor from kilogram to gigagram

The per cápita waste generation used is the same value used in category 4A solid waste disposal. The default value for Bfrac used is 0.6 as provided in the corresponding chapter of 2006 IPCC Guidelines.

89

Methodology and emission factors

Once the amount of total waste open burned is calculated, the emissions are calculated by applying an emission factor to the amount of waste burned in wet basis, for the case of CH4 and N2O, and by estimating the waste amount burned in dry basis for CO2 emissions as follows:

𝐶𝑂 𝐸𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑠 𝑆𝑊 ∗ 𝑑𝑚 ∗ 𝐶𝐹 ∗ 𝐹𝐶𝐹 ∗ 𝑂𝐹 ∗ 44/12

Where:

SWi = total amount of solid waste of type i (wet weight) incinerated or open-burned, Gg/yr dmi = dry matter content in the waste (wet weight) incinerated or open-burned, (fraction) CFi = fraction of carbon in the dry matter (total carbon content), (fraction) FCFi = fraction of fossil carbon in the total carbon, (fraction) OFi = oxidation factor, (fraction) 44/12 = conversion factor from C to CO2

i = type of waste incinerated/open-burned specified as follows: MSW: municipal solid waste; ISW: industrial solid waste,

The parameters used in the calculation are the following:

Oxidation factor: 0.58 Th coefficients provided by 2006 IPCC of Dry Matter Content, Fraction of Carbon in

Dry Matter and Fraction of Fossil Carbon in Total Carbon, which are specific to each component of the waste.

The emissions factors used for calculating the emissions are those proposed by 2006 IPCC guidelines for the tier 1 method: 6.5 g CH4/kg and 0.15 g N2O/kg.

Results

Table 97- Emission results – Open burning (data in Gg)

Year CO2 (Gg) CH4 (Gg) N2O (Gg) 1994 761.18 7.24 0.108

2005 924.79 8.79 0.131

2010 920.15 8.75 0.131 2011 927.26 8.82 0.132 2012 941.53 8.95 0.134 2013 962.68 9.16 0.137 2014 977.75 9.30 0.139 2015 981.77 9.34 0.139 2016 994.26 9.46 0.141

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4D. Wastewater treatment and discharge

Category 4D Wastewater treatment and discharge includes the emissions of CH4 and NO2 that occur when the wastewater is treated or disposed anaerobically. Wastewater originates from a variety of domestic, commercial and industrial sources and may be treated on site (uncollected), sewered to a centralized plant (collected) or disposed untreated nearby or via an outfall.

Activity data

Table 98 - Activity data domestic wastewater

Year Organically degradable material in wastewater (TOW) (kg BOD/yr)

Average annual per capita protein generation (kg/person/yr)

1994 194864907.9 15.57 2005 253164000 20.81 2010 260040819 22.05 2011 263985520 22.42 2012 269740000 22.79 2013 276167760 23.17 2014 280886808.5 23.54 2015 282462951.5 23.92 2016 286515162.6 24.29

The Organically degradable material in wastewater (TOW), has been calculated as follows, using the value “collected” for the adjustment of industrial wastewater and the BOD value provided for “Asia, Middle East, Latin America”:

𝑇𝑂𝑊 𝑃 ∗ 𝐵𝑂𝐷 ∗ 0.001 ∗ 𝐼 ∗ 365 Where:

TOW = total organics in wastewater in inventory year, kg BOD/yr P = country population in inventory year, (person) BOD = country-specific per capita BOD in inventory year, g/person/day 0.001 = conversion from grams BOD to kg BOD I = correction factor for additional industrial BOD discharged into sewers (for collected the default is 1.25, for uncollected the default is 1.00)

The default factor for BOD used is 40 kg BOD/cap/day extracted from Table 6.4 IPCC 2006. Value for Asia, Middle East, Latin America.

The data on Average annual per capita protein generation is provided by FAO for years 1990-92, 1995-97, 2000-02 and 2005-07. Intermediate years have been interpolated. The years 2007-2016 have been extrapolated using the expression of trend of the time series:

𝑌 0.3745𝑋 730.7

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Methodology and emission factors

The Tier 1 methodology provided by IPCC 2006 has been followed for estimating the emissions of both CH4 and N2O. For the emissions of CH4, the following equation has been used:

𝐶𝐻 𝐸𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑠 𝑈 ∗ 𝑇 , ∗ 𝐸𝐹,

𝑇𝑂𝑊 𝑆 𝑅

Where:

TOW = total organics in wastewater in inventory year, kg BOD/yr S = organic component removed as sludge in inventory year, kg BOD/yr Ui = fraction of population in income group i in inventory year Ti,j = degree of utilisation of treatment/discharge pathway or system, j, for each income group fraction i in inventory

year i = income group: rural, urban high income and urban low income j = each treatment/discharge pathway or system EFi,j = emission factor, kg CH4/kg BOD R = amount of CH4 recovered in inventory year, kg CH4/yr

The previous equation is complemented with the following expression for estimating the emission factor:

𝐸𝐹 𝐵 ∗ 𝑀𝐶𝐹 Where: j = each treatment/discharge pathway or system Bo = maximum CH4 producing capacity, Kg CH4/kg BOD MCFj = methane correction factor

For the calculation of the CH4 emissions, the assumptions made regarding the split of type of discharges for rural and urban population are contained in table Wastewater discharges typology above, so the corresponding coefficients of 2006 IPCC Guidelines have been used for calculating the emission factor by treatment.

The final emission factors used for estimating CH4 emissions are the following:

Table 99 - Emission factors used – CH4 emissions in domestic wastewater

Type of treatment 

Methane correction factor for each treatment system (MCF) 

Maximum methane producing capacity (Bo) (kg CH4/kg BOD) 

Emission factor (EF) (kg CH4/kg BOD) 

Untreated‐sea,river,lake  0.1  0.6  0.060 

Untreated‐flowing sewer  0  0.6  0 

Treated‐septic system  0.5  0.6  0.3 

Treated‐Latrine with sediments removal  0.1  0.6  0.060 

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For the case of N2O, the following expression has been used:

𝑁 𝑃 ∗ 𝑃𝑟𝑜𝑡𝑒𝑖𝑛 ∗ 𝐹 ∗ 𝐹 ∗ 𝐹 𝑁

Where: NEFFLUENT = total annual amount of nitrogen in the wastewater effluent, kg N/yr P = human population Protein = annual per capita protein consumption, kg/person/yr FNPR = fraction of nitrogen in protein, default = 0.16, kg N/kg protein FNON-CON = factor for non-consumed protein added to the wastewater FIND-COM = factor for industrial and commercial co-discharged protein into the sewer system NSLUDGE = nitrogen removed with sludge (default = zero), kg N/yr

Results

Table 100 - Emissions in domestic wastewater (Gg)

Year CH4 (Gg) N2O (Gg) 1994 23 0.29

2005 43 0.50 2010 49 0.54 2011 51 0.56 2012 53 0.58 2013 56 0.61 2014 58 0.63 2015 61 0.64 2016 62 0.66

3.6.4. Waste emissions trends

The GHG emissions of the waste sector are driven by the increase of urban population, along the improvements in sanitation and waste management.

Table 101 - Trend of emissions (GHG, Gg CO2-eq)

Inventory Sector 1994 2000 2005 2010 2015 2016

4A1 Solid waste disposal 605.14 760.99 940.47 1 138.11 1 396.46 1 444.85 4B2 Biological treatment 8.81 10.57 11.74 12.99 13.69 13.92 4C2 Open Burning 974.26 1 106.75 1 183.79 1 177.84 1 256.76 1 272.76 4D1 Domestic wastewater 660.26 960.46 1 215.79 1 393.58 1 710.77 1 734.93 Total 2 248.46 2 838.77 3 351.78 3 722.53 4 377.68 4 466.45

93

Figure 24 – GHG emissions in the waste sector - 1994-2016 (Gg CO2-eq)

As illustrated in the previous figure, waste GHG emissions show an increasing trend in all categories. The main contributor to the emissions of the sector is category 4D1 Domestic wastewate, with a contribution that ranges from a 29.4% in 1994 to a 38.8% in 2016. The increasing emissions of this category are explained by the expansion of the use of latrines in rural areas. The use of sanitary latrines involve higher methane emissions compared to other practices such as the discharges in lakes and rivers. The second contributor the waste GHG emissions is solid waste disposal, with a contribution that ranges from a 26.9% in 1994 to a 32.3% in 2016. The increasing emissions of this category are driven by the improvements in the waste management systems, particularly the shift from un-managed to managed landfills. Even this is a significant improvement for the country, the GHG emissions associated have growth, as the methane emissions associated to aerobic managed sites are significantly higher than the emissions for un-managed landfills11. The third contributor to waste emissions is open burning of waste, which a contribution than ranges from a 43.3% in 1994 to a 28.5 in 2016. The contribution has been reduced maninly driven by the migration of population from rural to urban areas, where open burning is a practice less extended among population. Finally, biological treatment of waste has a very low contribution to waste emissions, with a contribution that ranges from a 0.4% in 1994 to a 0.3% in 2016.

Regarding the contribution of each gas to total GHG emissions, the following table show the detailed evolution of the split of greenhous gases for the entire time period.

11 The methane correction factors provided by 2006 IPCC Guidelines for unmanaged sites are significantly lower than those for managed sites, affecting the final GHG emissions estimated.

0.00

500.00

1000.00

1500.00

2000.00

2500.00

3000.00

3500.00

Gg 

4A Solid waste disposal 4B Biological treatment

4C Incineration and open burning 4D Wastewater treatment

94

Table 102 - Percentage of emissions by gas (%)

Inventory Sector 1994 2000 2005 2010 2015 2016 CH4 60.7% 63.7% 66.7% 69.8% 72.1% 72.3% CO2 33.9% 30.5% 27.6% 24.7% 22.4% 22.3% N2O 5.4% 5.9% 5.7% 5.5% 5.4% 5.5% Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

Note  –  This  contribution  is  calculated  converting  first  the  emissions  of  each  gas  to  CO2‐eq  using  global warming 

potentials 

The gas which is predominant in the sector is CH4 followed by CO2.

The following table shows the emissions of each gas for the entire time series, in terms of mass of emissions of each gas:

Table 103 - Emissions by gas (Gg)

Gas 1994 2000 2005 2010 2015 2016

CO2 761.18 864.63 924.79 920.15 981.77 994.26 CH4 54.6 72.3 89.4 103.9 126.3 129.1 N2O 0.41 0.56 0.65 0.69 0.80 0.82 HFC NA NA NA NA NA NA NOx NA NA NA NA NA NA CO NA NA NA NA NA NA NMVOC NA NA NA NA NA NASO2 NA NA NA NA NA NA SF6 NA NA NA NA NA NA

3.7. Key category assessment and uncertainty analysis

3.7.1. Key category assessment

The 2006 IPCC Guidelines define key category (KC) as “(…) one that is prioritised within the national inventory system because its estimate has a significant influence on a country’s total inventory of greenhouse gases in terms of the absolute level, the trend, or the uncertainty in emissions and removals. Whenever the term key category is used, it includes both source and sink categories. (…)”

As far as possible, key categories should receive special consideration in terms of three important inventory aspects.

Firstly, identification of key categories in national inventories enables limited resources available for preparing inventories to be prioritised.

Secondly, in general, more detailed higher tier methods should be selected for key categories.

Thirdly, it is good practice to give additional attention to key categories with respect to quality assurance and quality control (QA/QC)

The general approach for identifying key categories is to identify KC in terms of their contribution to the absolute level of national emissions and removals. For the inventories considering time

95

series, the quantitative determination of key categories should include an evaluation of both the absolute level and the trend of emissions and removals.

The 2006 IPCC approach 1 have been used to identify key categories, for both the level and the trend. The following is a description of the methodology followed:

Level assessment

The contribution of each source or sink category to the total national inventory level is calculated according to the following equation:

𝐿 ,𝐸 ,

∑ 𝐸 ,

𝑊ℎ𝑒𝑟𝑒:

𝐿 , 𝑙𝑒𝑣𝑒𝑙 𝑎𝑠𝑠𝑒𝑠𝑠𝑚𝑒𝑛𝑡 𝑓𝑜𝑟 𝑠𝑜𝑢𝑟𝑐𝑒 𝑜𝑟 𝑠𝑖𝑛𝑘 𝑥 𝑖𝑛 𝑙𝑎𝑡𝑒𝑠𝑡 𝑖𝑛𝑣𝑒𝑛𝑡𝑜𝑟𝑦 𝑦𝑒𝑎𝑟 𝐸 , 𝑎𝑏𝑠𝑜𝑙𝑢𝑡𝑒 𝑣𝑎𝑙𝑢𝑒 𝑜𝑓 𝑒𝑚𝑖𝑠𝑠𝑖𝑜𝑛 𝑜𝑟 𝑟𝑒𝑚𝑜𝑣𝑎𝑙 𝑒𝑠𝑡𝑖𝑚𝑎𝑡𝑒 𝑜𝑓 𝑠𝑜𝑢𝑟𝑐𝑒 𝑜𝑟 𝑠𝑖𝑛𝑘 𝑐𝑎𝑡𝑒𝑜𝑔𝑦 𝑥 𝑖𝑛 𝑦𝑒𝑎𝑟 𝑡

𝐸 , 𝑡𝑜𝑡𝑎𝑙 𝑐𝑜𝑛𝑡𝑟𝑖𝑏𝑢𝑡𝑖𝑜𝑛, 𝑤ℎ𝑖𝑐ℎ 𝑖𝑠 𝑡ℎ𝑒 𝑠𝑢𝑚 𝑜𝑓 𝑡ℎ𝑒 𝑎𝑏𝑠𝑜𝑙𝑢𝑡𝑒 𝑣𝑎𝑙𝑢𝑒𝑠 𝑜𝑓 𝑒𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑠 𝑎𝑛𝑑 𝑟𝑒𝑚𝑜𝑣𝑎𝑙𝑠 𝑖𝑛 𝑦𝑒𝑎𝑟 𝑡

Trend assessment

The Trend Assessment is calculated according to the following equation:

𝑇 ,𝐸 ,

∑ 𝐸 , ∙

𝐸 , 𝐸 ,

𝐸 ,

∑ 𝐸 , ∑ 𝐸 ,

∑ 𝐸 ,

𝑊ℎ𝑒𝑟𝑒:

𝑇 , 𝑡𝑟𝑒𝑛𝑑 𝑎𝑠𝑠𝑒𝑠𝑠𝑚𝑒𝑛𝑡 𝑓𝑜𝑟 𝑠𝑜𝑢𝑟𝑐𝑒 𝑜𝑟 𝑠𝑖𝑛𝑘 𝑥 𝑖𝑛 𝑦𝑒𝑎𝑟 𝑡 𝑎𝑠 𝑐𝑜𝑚𝑝𝑎𝑟𝑒𝑑 𝑡𝑜 𝑡ℎ𝑒 𝑏𝑎𝑠𝑒 𝑦𝑒𝑎𝑟 𝑦𝑒𝑎𝑟 0 𝐸 , 𝑎𝑏𝑠𝑜𝑙𝑢𝑡𝑒 𝑣𝑎𝑙𝑢𝑒 𝑜𝑓 𝑒𝑚𝑖𝑠𝑠𝑖𝑜𝑛 𝑜𝑟 𝑟𝑒𝑚𝑜𝑣𝑎𝑙 𝑒𝑠𝑡𝑖𝑚𝑎𝑡𝑒 𝑜𝑓 𝑠𝑜𝑢𝑟𝑐𝑒 𝑜𝑟 𝑠𝑖𝑛𝑘 𝑐𝑎𝑡𝑒𝑜𝑔𝑦 𝑥 𝑖𝑛 𝑦𝑒𝑎𝑟 0

𝐸 , 𝑎𝑛𝑑 𝐸 , 𝑟𝑒𝑎𝑙 𝑣𝑎𝑙𝑢𝑒𝑠 𝑜𝑓 𝑒𝑠𝑡𝑖𝑚𝑎𝑡𝑒 𝑜𝑓 𝑠𝑜𝑢𝑟𝑐𝑒 𝑜𝑟 𝑠𝑖𝑛𝑘 𝑐𝑎𝑡𝑒𝑔𝑜𝑟𝑦 𝑋 𝑖𝑛 𝑦𝑒𝑎𝑟𝑠 𝑡 𝑎𝑛𝑑 0, 𝑟𝑒𝑠𝑝𝑒𝑐𝑡𝑖𝑣𝑒𝑙𝑦. 𝐸 , 𝑎𝑛𝑑 𝐸 , 𝑇𝑜𝑡𝑎𝑙 𝑖𝑛𝑐𝑣𝑒𝑛𝑡𝑜𝑦 𝑒𝑠𝑡𝑖𝑚𝑎𝑡𝑒𝑠 𝑖𝑛 𝑦𝑒𝑎𝑟𝑠 𝑡 𝑎𝑛𝑑 0, 𝑟𝑒𝑠𝑝𝑒𝑐𝑡𝑖𝑣𝑒𝑙𝑦.

Disaggregation level

The results of the key category identification will be most useful if the analysis is done at the appropriate disaggregation level of categories. The assessment performed has followed, as far as possible, the suggested aggregation level of analysis for approach 1 provided by 2006 IPCC Guidelines. The exception is the Forestry and Other Land Uses subsector. In this sector, the break down in more disaggregated categories has not been possible because of the data available.

96

Results

Table 104 - Summary of key categories identified by method

IPCC category

Name Gas With FOLU Without FOLU

L2016 L1994 Trend L2016 L1994 Trend

3B Land CO2 X  X  X          

3A1 Enteric Fermentation CH4 X  X  X  X  X  X 

1A1- Solid Energy industries - solid fuels CO2 X     X  X     X 

3C7 Rice cultivations CH4 X  X  X  X  X  X 

2A1 Cement production CO2 X      X  X     X 

1A3b - liquid Road transport - liquid fuels CO2 X  X  X  X  X  X 

3A2 Manure Management N2O    X  X  X  X  X 

4C2 Open burning CO2    X  X  X  X  X 

3C4 Direct N2O Emissions from managed soils

N2O    X  X  X  X  X 

3A2 Manure Management CH4    X  X  X  X  X 

2F1 Refrigeration and air conditioning HFC          X     X 

1A2 - Liquid

Manufacturing industries and construction - Liquid fuels

CO2          X     X 

1A1- biomass Energy industries - biomass CH4       X     X  X 

1A1 - liquid Energy industries - liquid fuels CO2          X     X 

4A1 Solid waste disposal CH4 X  X  X  X  X  X 

4D1 Domestic wastewater CH4       X  X     X 

3C5 Indirect N2O Emissions from managed soils

N2O       X  X  X  X 

1A4 - biomass Other sectors - biomass CH4       X  X  X  X 

4C2 Open burning CH4             X    

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Table 105 - Key category analysis with FOLU – Level (2016)

IPCC category  Name  Gas Emissions year 2016 

Assessment for year 2016 

Cummulative total 2016 

KCA order 2016 

3B Land CO2 131011.24 0.79 0.79 1 3C7 Rice cultivations CH4 11323.14 0.07 0.86 2

1A3b – liquid Road transport - liquid fuels CO2 4933.16 0.03 0.89 3

3A1 Enteric Fermentation CH4 4188.38 0.03 0.92 4

1A1- Solid Energy industries - solid fuels CO2 2663.57 0.02 0.93 5

2A1 Cement production CO2 1420.96 0.01 0.95 6 4A1 Solid waste disposal CH4 1345.77 0.01 0.957 7

Table 106 - Key category analysis with FOLU– Level (1994)

IPCC category  Name  Gas Emissions year 1994 

Assessment for year 1994 

Cummulative total 2016 

KCA order 1994 

3B Land CO2 27018.62 0.63 0.626 1 3C7 Rice cultivations CH4 4602.85 0.11 0.733 2 3A1 Enteric Fermentation CH4 4249.36 0.10 0.831 3

1A3b – liquid Road transport - liquid fuels CO2 1849.58 0.04 0.874 4

3C4 Direct N2O Emissions from managed soils N2O 684.01 0.02 0.900 5

3A2 Manure Management N2O 649.45 0.02 0.915 6 4C2 Open burning CO2 623.20 0.01 0.930 7 4A1 Solid waste disposal CH4 539.20 0.01 0.942 8

3A2 Manure Management CH4 471.76 0.01 0.954 9 Table 107 - Key category analysis with FOLU– Trend (1994-2016)

IPCC category

Name GasTrend

assessment

% Contribution to the

trend

Total cumulative

trend

Order trend

3B Land CO2 0.64 0.42 0.424 1 3A1 Enteric Fermentation CH4 0.28 0.19 0.610 2 3C7 Rice cultivations CH4 0.15 0.10 0.707 3 1A1- Solid Energy industries - solid fuels CO2 0.06 0.04 0.748 4 1A3b – liquid Road transport - liquid fuels CO2 0.05 0.03 0.786 5 3A2 Manure Management N2O 0.04 0.03 0.814 6

3C4 Direct N2O Emissions from managed soils N2O 0.04 0.03 0.841 7

4C2 Open Burning CO2 0.04 0.02 0.865 8 2A1 Cement production CO2 0.03 0.02 0.887 9 3A2 Manure Management CH4 0.03 0.02 0.907 10 4A1 Solid waste disposal CH4 0.02 0.01 0.918 11 1A1 Energy industries – biomass CH4 0.02 0.01 0.929 12 4D1 Domestic wastewater CH4 0.02 0.01 0.940 13

3C5 Indirect N2O Emissions from managed soils N2O 0.01 0.01 0.950 14

1A4 - biomass Other sectors - biomass CH4 0.01 0.01 0.957 15

98

Table 108 - Key category analysis without FOLU – Level (2016)

IPCC category

Name Gas Emissions year 2016

Assessment for year

2016

Cummulative total 2016

KCA order 2016

3C7 - Rice cultivations

Rice cultivations CH4 11323.14 0.34 0.34 1

1A3b - liquid Road transport - liquid fuels CO2 4933.16 0.15 0.49 2 3A1 - Enteric Fermentation

Enteric Fermentation CH4 4188.38 0.13 0.62 3

1A1- Solid Energy industries - solid fuels CO2 2663.57 0.08 0.70 4 2A1 Cement production CO2 1420.96 0.04 0.75 5 4A1 - Solid waste disposal

Solid waste disposal CH4 1345.77 0.04 0.79 6

3C4 - Direct N2O Emissions from managed soils

Direct N2O Emissions from managed soils

N2O 943.80 0.03 0.82 7

4C2 - Open burning

Open burning CO2 814.55 0.02 0.84 8

3A2 - Manure Management

Manure Management N2O 663.06 0.02 0.86 9

1A2 - Liquid Manufacturing industries and construction - Liquid fuels CO2 603.88 0.02 0.88 10

3A2 - Manure Management

Manure Management CH4 533.10 0.02 0.90 11

3C5 - Indirect N2O Emissions from managed soils

Indirect N2O Emissions from managed soils

N2O 404.22 0.01 0.91 12

4D1 - Domestic wastewater

Domestic wastewater CH4 401.48 0.01 0.92 13

2F1 Refrigeration and air conditioning HFC 371.95 0.01 0.93 14 1A1 - liquid Energy industries - liquid fuels CO2 326.84 0.01 0.94 15 1A4 - biomass Other sectors - biomass CH4 265.56 0.01 0.95 16

Table 109 - Key category analysis without FOLU– Level (1994)

IPCC category

Name Gas Emissions year 1994

Assessment for year

1994

Cummulative total 1994

KCA order 1994

3C7 - Rice cultivations

Rice cultivations CH4 11323.14 0.34 0.34 1

3A1 - Enteric Fermentation

Enteric Fermentation CH4 4,249.36 0.27 0.566 2

1A3b - liquid Road transport - liquid fuels CO2 1,849.58 0.12 0.684 3 3C4 - Direct N2O Emissions from managed soils

Direct N2O Emissions from managed soils

N2O 684.01 0.04 0.727 4

3A2 - Manure Management

Manure Management N2O 649.45 0.04 0.769 5

4C2 - Open burning

Open burning CO2 623.20 0.04 0.809 6

4A1 - Solid waste disposal

Solid waste disposal CH4 539.20 0.03 0.843 7

3A2 - Manure Management

Manure Management CH4 471.76 0.03 0.873 8

99

IPCC category

Name Gas Emissions year 1994

Assessment for year

1994

Cummulative total 1994

KCA order 1994

4D1 - Domestic wastewater

Domestic wastewater CH4 286.25 0.02 0.8915 9

3C5 - Indirect N2O Emissions from managed soils

Indirect N2O Emissions from managed soils

N2O 265.93 0.02 0.909 10

1A1- biomass Energy industries - biomass CH4 250.28 0.02 0.925 11 1A4 - biomass Other sectors - biomass CH4 195.49 0.01 0.937 12 4C2 - Open burning

Open burning CH4 180.88 0.01 0.949 13

3C6 - Indirect N2O Emissions from manure management

Indirect N2O Emissions from manure management

N2O 144.08 0.01 0.958 14

Table 110 - Key category analysis without FOLU– Trend (1994-2016)

IPCC category

Name GasTrend

assessment

% Contributio

n to the trend

Total cumulative

trend

Order trend

3A1 - Enteric Fermentation

Enteric Fermentation CH4 0.30 0.29 0.290 1

1A1- Solid Energy industries - solid fuels CO2 0.17 0.16 0.453 2 3C7 - Rice cultivations

Rice cultivations CH4 0.11 0.10 0.554 3

2A1 Cement production CO2 0.09 0.09 0.641 4 1A3b - liquid Road transport - liquid fuels CO2 0.07 0.06 0.705 5 3A2 - Manure Management

Manure Management N2O 0.04 0.04 0.748 6

4C2 - Open burning

Open burning CO2 0.03 0.03 0.778 7

3C4 - Direct N2O Emissions from managed soils

Direct N2O Emissions from managed soils

N2O 0.03 0.03 0.808 8

3A2 - Manure Management

Manure Management CH4 0.03 0.03 0.836 9

2F1 Refrigeration and air conditioning HFC 0.02 0.02 0.859 10

1A2 - Liquid Manufacturing industries and construction - Liquid fuels CO2 0.02 0.02 0.881 11

1A1- biomass Energy industries - biomass CH4 0.02 0.02 0.898 12 1A1 - liquid Energy industries - liquid fuels CO2 0.01 0.01 0.912 13 4A1 - Solid waste disposal

Solid waste disposal CH4 0.01 0.01 0.925 14

4D1 - Domestic wastewater

Domestic wastewater CH4 0.01 0.01 0.937 15

3C5 - Indirect N2O Emissions from managed soils

Indirect N2O Emissions from managed soils

N2O 0.01 0.01 0.947 16

1A4 - biomass Other sectors - biomass CH4 0.01 0.01 0.956 17

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3.7.2. Uncertainty analysis

The following table shows the uncertainty values estimated by CRF category of the inventory. Specifically, the following table shows:

‐ The uncertainty of the activity data and emission factor by emission source. The source of all the uncertainty values for the energy sector is IPCC 2006. For the selection of the uncertainty among those provided by IPCC 2006, the criteria have been based on the conservative principle, using the upper values of the ranges by default.

‐ The combined uncertainty calculated with the uncertainty of the activity data and emission factor and the emission level and trend, where appropriate,

‐ The calculation for the sensitivity type A and B, based on the equations provided in 2016 IPCC guidelines.

‐ The uncertainty in the total level and trend of the emissions of the inventory.

The methodology followed is the tier 1 provided by 2006 IPCC Guidelines. The following table and the associated calculations are extracted from the table 3.2, volume 1, chapter 3 of 2006 IPCC Guidelines. A complete description of each of the terms of the table is available in this chapter of the 2006 IPCC Guidelines.

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Table 111 – Uncertainty of the inventory

IPCC category  Gas Base year emissions 

2016 emissions 

Activity data uncertainty 

Emission factor 

Uncertainty 

Combined uncertainty 

Contribution to variance by 

category in year 2016 

Type A sensitivity 

Type B sensitivity 

Uncertainty in trend by EF 

Uncertainty in trend by AD 

Uncertainty introduced into the 

trend in total national emissions 

    Gg of CO2‐eq  %  %  %    %  %  %  %   

1A1 -Energy industries– Solid

CO2 0.00  2 663.57  5  7  9  0.020  0.062  0.062  0.437  0.312  0.288 

1A1 -Energy industries – Solid

CH4 0.00  0.69  5  100  100  0.000  0.000  0.000  0.002  0.000  0.000 

1A1 -Energy industries – Solid

N2O 0.00  12.39  5  75  75  0.000  0.000  0.000  0.022  0.001  0.000 

1A1 -Energy industries – Liquid

CO2 48.28  326.84  5  7  9  0.000  0.003  0.008  0.023  0.038  0.002 

1A1 -Energy industries – Liquid

CH4 0.05  0.32  5  100  100  0.000  0.000  0.000  0.000  0.000  0.000 

1A1 -Energy industries – Liquid

N2O 0.11  0.76  5  75  75  0.000  0.000  0.000  0.001  0.000  0.000 

1A1 -Energy industries – Biomass

CH4 250.28  250.32  60  100  117  0.032  ‐0.017  0.006  ‐1.666  0.352  2.899 

1A1 -Energy industries – Biomass

N2O 0.15  0.70  60  75  96  0.000  0.000  0.000  0.000  0.001  0.000 

1A2 -Manufacturing Industries– Solid

CO2 0.00  68.40  3  7  8  0.000  0.002  0.002  0.011  0.005  0.000 

1A2 -Manufacturing Industries – Solid

CH4 0.00  0.02  3  100  100  0.000  0.000  0.000  0.000  0.000  0.000 

1A2 -Manufacturing Industries – Solid

N2O 0.00  0.32  3  75  75  0.000  0.000  0.000  0.001  0.000  0.000 

1A2 -Manufacturing Industries – Liquid

CO2 114.84  603.88  3  7  8  0.001  0.004  0.014  0.027  0.042  0.003 

1A2 -Manufacturing Industries – Liquid

CH4 0.12  0.60  3  100  100  0.000  0.000  0.000  0.000  0.000  0.000 

1A2 -Manufacturing Industries – Liquid

N2O 0.28  1.42  3  75  75  0.000  0.000  0.000  0.001  0.000  0.000 

1A2 -Manufacturing Industries – Biomass

CH4 27.48  27.63  60  100  117  0.000  ‐0.002  0.001  ‐0.183  0.039  0.035 

1A2 -Manufacturing Industries – Biomass

N2O 43.67  43.92  60  75  96  0.001  ‐0.003  0.001  ‐0.218  0.062  0.051 

1A3a - Domestic aviation– liquid

CO2 2.48  59.87  5  7  9  0.000  0.001  0.001  0.008  0.007  0.000 

102

IPCC category  Gas Base year emissions 

2016 emissions 

Activity data uncertainty 

Emission factor 

Uncertainty 

Combined uncertainty 

Contribution to variance by 

category in year 2016 

Type A sensitivity 

Type B sensitivity 

Uncertainty in trend by EF 

Uncertainty in trend by AD 

Uncertainty introduced into the 

trend in total national emissions 

    Gg of CO2‐eq  %  %  %    %  %  %  %   

1A3a - Domestic aviation – liquid

CH4 0.00  0.01  5  100  100  0.000  0.000  0.000  0.000  0.000  0.000 

1A3a - Domestic aviation – liquid

N2O 0.02  0.50  5  75  75  0.000  0.000  0.000  0.001  0.000  0.000 

1A3b -Road transport– liquid

CO2 1 849.58  4 933.16  5  7  9  0.067  ‐0.051  0.116  ‐0.356  0.578  0.461 

1A3b -Road transport – liquid

CH4 12.85  30.25  5  100  100  0.000  0.000  0.001  ‐0.045  0.004  0.002 

1A3b -Road transport – liquid

N2O 27.11  70.42  5  75  75  0.001  ‐0.001  0.002  ‐0.059  0.008  0.004 

1A4 -Others– liquid CO2 91.55  189.57  15  7  17  0.000  ‐0.004  0.004  ‐0.027  0.067  0.005 

1A4 -Others – liquid CH4 0.30  0.56  15  100  101  0.000  0.000  0.000  ‐0.001  0.000  0.000 

1A4 -Others – liquid N2O 0.21  0.35  15  75  76  0.000  0.000  0.000  ‐0.001  0.000  0.000 

1A4 -Others – biomass

CH4 195.49  265.56  60  100  117  0.036  ‐0.011  0.006  ‐1.137  0.373  1.432 

1A4 -Others – biomass

N2O 26.10  49.60  60  75  96  0.001  ‐0.001  0.001  ‐0.089  0.070  0.013 

2A1 – Cement CO2 0.00  1 420.96  10  10  14  0.015  0.033  0.033  0.333  0.333  0.222 

2D1 – Lubricants CO2 3.81  28.50  3  50  50  0.000  0.000  0.001  0.016  0.002  0.000 

2F - F-gases HFC 0.00  371.95  100  100  141  0.103  0.009  0.009  0.872  0.872  1.520 

3A1 - Enteric Fermentation

CH4 4 249.36  4 188.38  20  30  36  0.849  ‐0.284  0.098  ‐8.520  1.963  76.448 

3A2 - Manure Management

CH4 471.76  533.10  20  30  36  0.014  ‐0.030  0.012  ‐0.899  0.250  0.870 

3A2 - Manure Management

N2O 649.45  663.06  20  50  54  0.047  ‐0.043  0.016  ‐2.145  0.311  4.699 

3B – Land CO2 27 018.62  131 011.24 20  100  102  6,646  0.634  3.070  63.448  61.404  7 796 

3C1 - Emissions from biomass burning

CH4 68.32  84.19  100  50  112  0.003  ‐0.004  0.002  ‐0.209  0.197  0.083 

3C1 - Emissions from biomass burning

N2O 65.21  71.67  100  50  112  0.002  ‐0.004  0.002  ‐0.209  0.168  0.072 

3C3 - Urea application CO2 1.61  17.42  50  5  50  0.000  0.000  0.000  0.001  0.020  0.000 

103

IPCC category  Gas Base year emissions 

2016 emissions 

Activity data uncertainty 

Emission factor 

Uncertainty 

Combined uncertainty 

Contribution to variance by 

category in year 2016 

Type A sensitivity 

Type B sensitivity 

Uncertainty in trend by EF 

Uncertainty in trend by AD 

Uncertainty introduced into the 

trend in total national emissions 

    Gg of CO2‐eq  %  %  %    %  %  %  %   

3C4 - Direct N2O Emissions from managed soils

N2O 684.01  943.80  50  100  112  0.415  ‐0.039  0.022  ‐3.944  1.106  16.776 

3C5 - Indirect N2O Emissions from managed soils

N2O 265.93  404.22  50  100  112  0.076  ‐0.014  0.009  ‐1.446  0.474  2.315 

3C6 - Indirect N2O Emissions from manure management

N2O 144.08  168.68  50  100  112  0.013  ‐0.009  0.004  ‐0.901  0.198  0.852 

3C7 - Rice cultivations

CH4 4 602.85  11 323.14  10  75  76  27.330  ‐0.149  0.265  ‐11.156  2.654  131 

4A1 - Solid waste disposal

CH4 539.20  1 345.77  100  102  143  1.376  ‐0.017  0.032  ‐1.733  3.154  12.949 

4B2 – Composting CH4 5.13  7.90  100  5  100  0.000  0.000  0.000  ‐0.001  0.019  0.000 

4B2 – Composting N2O 3.67  5.65  100  5  100  0.000  0.000  0.000  ‐0.001  0.013  0.000 

4B2 - Anaerobic digestion

CH4 0.00  0.37  100  100  141  0.000  0.000  0.000  0.001  0.001  0.000 

4C2 - Open burning CO2 623.20  814.55  100  100  141  0.494  ‐0.037  0.019  ‐3.699  1.909  17.329 

4C2 - Open burning N2O 32.19  42.08  100  100  141  0.001  ‐0.002  0.001  ‐0.191  0.099  0.046 

4C2 - Open burning CH4 180.88  236.42  100  100  141  0.042  ‐0.011  0.006  ‐1.074  0.554  1.460 

4D1 – Domestic wastewater

CH4 286.25  401.48  59  117  131  0.103  ‐0.016  0.009  ‐1.913  0.555  3.969 

4D1 – Domestic wastewater

N2O 85.66  196.45  20  8  22  0.001  ‐0.003  0.005  ‐0.025  0.092  0.009 

 

National total 

emissions 42 672  163 883 

  Year 

uncertainty 81.72 

  Trend 

uncertainty89.84 

104

Energy sector

The following table shows a summary of the uncertainty values at category level*fuel*gas level for the energy sector:

Table 112 - Uncertainty in the energy sector

CRF category Gas AD

uncertainty (%)

EF uncertaint

y (%)

Combined uncertainty (%)

1A1 -Energy industries– Solid CO2 5 7 9 1A1 -Energy industries – Solid CH4 5 100 100 1A1 -Energy industries – Solid N2O 5 75 75 1A1 -Energy industries – Liquid CO2 5 7 9 1A1 -Energy industries – Liquid CH4 5 100 100 1A1 -Energy industries – Liquid N2O 5 75 75 1A1 -Energy industries – Biomass CO2 60 7 60 1A1 -Energy industries – Biomass CH4 60 100 117 1A1 -Energy industries – Biomass N2O 60 75 96 1A2 -Manufacturing Industries– Solid CO2 3 7 8 1A2 -Manufacturing Industries – Solid CH4 3 100 100 1A2 -Manufacturing Industries – Solid N2O 3 75 75 1A2 -Manufacturing Industries – Liquid CO2 3 7 8 1A2 -Manufacturing Industries – Liquid CH4 3 100 100 1A2 -Manufacturing Industries – Liquid N2O 3 75 75 1A2 -Manufacturing Industries – Biomass CO2 60 7 60 1A2 -Manufacturing Industries – Biomass CH4 60 100 117 1A2 -Manufacturing Industries – Biomass N2O 60 75 96 1A3a - Domestic aviation– liquid CO2 5 7 9 1A3a - Domestic aviation – liquid CH4 5 100 100 1A3a - Domestic aviation – liquid N2O 5 75 75 1A3b -Road transport– liquid CO2 5 7 9 1A3b -Road transport – liquid CH4 5 100 100 1A3b -Road transport – liquid N2O 5 75 75 1A4 -Others– liquid CO2 15 7 17 1A4 -Others – liquid CH4 15 100 101 1A4 -Others – liquid N2O 15 75 76 1A4 -Others – biomass CO2 60 7 60 1A4 -Others – biomass CH4 60 100 117 1A4 -Others – biomass N2O 60 75 96

The source of all the uncertainty values for the energy sector is IPCC 2006. For the selection of the uncertainty among those provided by IPCC 2006, the criteria have been based on the conservative principle, using the upper values of the ranges by default.

105

IPPU sector

The following table shows a summary of the uncertainty values at category *gas level for the IPPU sector:

Table 113 - Uncertainty in the IPPU sector

Category Gas AD

uncertainty (%)

EF uncertainty (%)

Combined uncertainty

(%) 2A1 – Cement production CO2 10 10 14 2D1 – Lubricants CO2 3 50 50 2F - Subst. for ODS (F-gases) HFC-125 100 100 141 2F - Subst. for ODS (F-gases) HFC143a 100 100 141 2F - Subst. for ODS (F-gases) HFC134a 100 100 141 2F - Subst. for ODS (F-gases) HFC-32 100 100 141 2F - Subst. for ODS (F-gases) HFC-227ea 100 100 141

The uncertainty values allocated in this sector are mainly based on expert judgment (based on 2006 IPCC guidance) rather than default values. The reason for that is the limited guidance provided by 2006 IPCC Guidelines. More information on uncertainties can be found on the IPPU work file, sheet “Uncertainty”.

Waste sector

The following table shows a summary of the uncertainty values at category*gas level for the waste sector:

Table 114 - Uncertainty in the waste sector

CRF category Gas

AD uncertainty (%)

EF uncertainty (%)

Combined uncertainty (%)

4A1 - Solid waste disposal CH4 100 102 143 4B2 – Composting CH4 100 5 100

4B2 – Composting N2O 100 5 100

4B2 - Anaerobic digestion CH4 100 100 141

4C2 - Open burning CO2 100 100 141

4C2 - Open burning N2O 100 100 141

4C2 - Open burning CH4 100 100 141 4D1 – Domestic wastewater CH4 59 117 130

4D1 – Domestic wastewater N2O

20 8 22

The uncertainty values allocated in this sector are mainly based on expert judgment (based on 2006 IPCC guidance) rather than default values. The reason for that is the limited guidance provided by 2006 IPCC Guidelines.

106

107

AFOLU sector

The following table shows a summary of the uncertainty values at category*gas level for the AFOLU sector:

Table 115 - Uncertainty in the waste sector

CRF category AD uncertainty (%)

EF uncertainty (%)

Combined uncertainty (%)

Enteric fermentation

3.A.1.a.i - Dairy Cows 20 30 36 3.A.1.a.ii - Other Cattle 20 30 36 3.A.1.b - Buffalo 20 30 36 3.A.1.c - Sheep 20 30 36 3.A.1.d - Goats 20 30 36 3.A.1.e - Camels 20 30 36 3.A.1.f - Horses 20 30 36 3.A.1.g - Mules and Asses 20 30 36 3.A.1.h - Swine 20 30 36 3.A.1.j – Other 20 30 36 Manure management – CH4

3.A.2.a.i - Dairy cows 20 30 36 3.A.2.a.ii - Other cattle 20 30 36 3.A.2.b - Buffalo 20 30 36 3.A.2.c - Sheep 20 30 36 3.A.2.d - Goats 20 30 36 3.A.2.e - Camels 20 30 36 3.A.2.f - Horses 20 30 36 3.A.2.g - Mules and Asses 20 30 36 3.A.2.h - Swine 20 30 36 3.A.2.i - Poultry 20 30 36 Manure management – N2O

3.A.2.a.i - Dairy cows 20 50 54 3.A.2.a.ii - Other cattle 20 50 54 3.A.2.b - Buffalo 20 50 54 3.A.2.c - Sheep 20 50 54 3.A.2.d - Goats 20 50 54 3.A.2.e - Camels 20 50 54 3.A.2.f - Horses 20 50 54 3.A.2.g - Mules and Asses 20 50 54 3.A.2.h - Swine 20 50 54 3.A.2.i - Poultry 20 50 54 3-B Land 20 100

3.C - Aggregate sources and non-CO2 emissions sources on land – CH4 3.C.1.b - Biomass burning in croplands 50 50 71 3.C.1.c - Biomass burning in grasslands 100 50 112

108

CRF category AD uncertainty (%)

EF uncertainty (%)

Combined uncertainty (%)

3.C - Aggregate sources and non-CO2 emissions sources on land – N2O3.C.1.b - Biomass burning in croplands 50 50 71 3.C.1.c - Biomass burning in grasslands 100 50 112

3.C.3 - Urea application 50 5 50 3.C.4 - Direct N2O Emissions from managed soils 50 100 112 3.C.5 - Indirect N2O Emissions from managed soils 50 100 112 3.C.6 - Indirect N2O Emissions from manure management 50 100 112

3.C.7 - Rice cultivations 10 75 76

The source of all the uncertainty values for categories included within 3A Livestock is IPCC 2006. For the selection of the uncertainty among those provided by IPCC 2006, the criteria have been based on the conservative principle, using the upper values of the ranges by default.

Conversely, the uncertainty values allocated in 3B Land and 3C Aggregate sources and non-CO2 emissions sources on land are mainly based on expert judgment (based on 2006 IPCC guidance) rather than default values. The reason for that is the limited guidance provided by 2006 IPCC Guidelines. More information on uncertainties can be found on the results in the AFOLU work files, sheet “Uncertainty”.

3.8. Results of the QA/QC

Quality Control

Quality Control (QC) is a system of routine technical activities aimed at assessing and ensuring the quality of the inventory as it is compiled. The quality of control needs to be developed in all steps of the inventory compilation, from the data gathering to the submission of reports. QC is developed in line with the specificities defined in the QA/QC plan (see section on the QA/QC plan within the National System above).

In its 2019 edition of the GHG emission inventory, Cambodia has developed two types of quality control procedures: general QC procedures and category specific QC procedures, as proposed by 2016 IPCC Guidelines.

General QC procedures include generic quality checks related to calculations, data processing, completeness, and documentation that are applicable to all inventory source and sink categories.

For the general QC procedures, a QC template was used by national compilers for reviewing the GHG emission compilation of all sectors. The following table shows the QC procedures checked by national compilers.

109

Table 116 – General QC Procedures

QC activity Procedures

Documentation

Base information Detailed description of the references of the base information used

Methodological coefficients Detailed description of the references of the methodological coefficients used

Conversion coefficients Detailed reference of all the conversion coefficients used

Units Documentation of the units of the series

Data Transcription Base information Errors in the transcription of the base information

Methodological coefficients The methodological coefficients must coincide with the reference sources

Conversion coefficients The conversion coefficients coincide with the reference sources (if possible)

Units The units of the original data are correct

Emissions calculations

Last inventory year Check current year estimates against previous years (if available) and investigate unexplained departures from trend

Emission factor Assess representativeness of emission factors, given national circumstances and analogous emissions data

Conversion factors Check that conversion factors are correct

Time series

Review of the accuracy and temporal coherence of the time series. Check that there are no errors in the calculation, and examine the temporal coherence of the series, looking for anomalous data in the time series and comparing with indicators (if possible)

Uncertainty

Assignment of uncertainties The assigned uncertainties (tab "Uncertainty") are consistent with IPCC 2006

The QC procedures of the template were checked in all inventory categories, specifying the errors found, proposing corrective actions and making observations, if appropriate.

The following issues were identified and corrected as a result of the general QC procedures:

i) The emission factors for category 1A4 were linked to those of category 1A1. ii) There was an error in the conversion performed in the calculation of the biogas

consumption iii) There was an error in the formulae for the calculation of domestic wastewater.

110

iv) There was an error in the amount of gases used as a raw data for the calculation of emissions within category 2F.

An additional general QC procedure was carried out in the 2019 edition of the inventory. The GHG emission calculations were performed in the 2006 IPCC software and the results were compared against the results obtained in the Excel worksheets. The differences between both approached in terms of GHG emissions were below 2% in all cases.

Category specific QC procedures complements general inventory QC procedures and are directed at specific types of data used in the methods for individual source or sink categories. These procedures require knowledge of the specific category, the types of data available and the parameters associated with emissions or removals and are performed in addition to the general QC checks. The category specific procedures were carried out by International inventory compilers during the inventory development. The main category specific procedures developed were the following:

Energy sector: reference vs sectoral approach; comparison of the data provided by the different sources of information; In the comparison of the reference approach, the differences for some years were above 5%. See methodological section for the energy sector for more detailed information.

IPPU sector: comparison of tier 1 and tier 2 estimates in cement production. As there are data on clinker production from one cement plant as well as data on cement production, it was verified that the differences between estimations are due just to the different coefficients used (95% clinker content vs national specific clinker quantities).

Waste sector: Comparison of the default rate provided by 2006 IPCC for industrial waste generation against a national rate estimated using real data on industrial waste generated. Two conclusions were raised from this QC: i) the default value provided by IPCC is not adequate for the conditions of Cambodia as the results on emissions were higher than those of municipal solid waste; ii) The scope of the data on industrial waste generated is not 100% of the activity data. As a result of the QC, the rate estimated using national data was used, but this issue needs to be improved in future editions of the inventory.

111

Quality Assurance

In the international team a peer reviewer expert was assigned by sector to undertake checks, propose improvements and ensure the quality of the inventory. These checks have been designed to verify the transparency, accuracy, consistency, comparability and completeness of the information submitted and include:

a) an assessment whether all emission source categories and gases are reported; b) an assessment whether emissions data time series are consistent; c) an assessment whether implied emission factors are comparable to the emissions

factors of other countries with similar national circumstances such as Vietnam and also taking the IPCC default emission factors into account;

d) an assessment of the use of ‘Not Estimated’ notation keys where IPCC tier 1 methodologies exist;

e) an analysis of recalculations performed for the inventory submission, compared to the inventories presented in previous national communications;

f) a comparison of the national data using both different national data sources and international data sources when available;

g) a comparison of the results of the reference approach with the sectoral approach for the energy sector;

h) an assessment whether there were potential overestimations or underestimations relating to a key category in the inventory.

In particular, the peer reviewers checked if the international team in charge of the inventory compilation had implemented the following activities:

Source data received are traceable back to their source in the compilation system. The mechanisms for this are spreadsheet notes, and a common system of data referencing of activity data and emission factors in each sector.

Checks are undertaken at each stage of the inventory compilation – on receipt of the data, after each calculation step and at the end of the process before dissemination.

Calculations are also checked and the checks applied are described in the QA/QC Plan.

Checks are made on the inventory comparing the emissions of the whole time series and looking for explanations of the trend to ensure that large inter-annual variations have been investigated.

Compare the reference and the sectoral approach in the energy sector and look for explanations in case of large discrepancies (the total emissions by fuel, must be consistent with the total emissions by source).

All spreadsheets are subject to second-person checking prior to data uploading to the IPCC software.

As an additional quality check, the national emission estimates were also prepared via the IPCC software by introducing the activity data and emission factors.

The national report provides full details of inventory estimation methodologies by source category. The report includes summaries of key data sources and significant revisions to methods and historic data, where appropriate. It also describes the assumptions used in the compilation.

The uncertainty analysis and the key category analysis for the greenhouse gas inventory is detailed within the National Inventory Report.

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The national report includes a programme of continuous improvement. At the end of each reporting cycle it is planned that all the database files, spreadsheets,

on-line manual, electronic source data, paper source data, output files, etc, are in effect frozen and archived. An annual report outlining the methodology of the inventory and data sources is produced. Electronic information is stored on hard disks that are regularly backed up.

Final quality assurance checks: Official consideration and approval of the inventory

The official approval procedure of the inventory consisted in one-month period of interactions between the technical international consultants and the national team who held meetings by sector with the most relevant national stakeholders. During this period, the international team revised the inventory according to the observations and recommendations of the competent authority. On the basis of this interaction process, the final version of the inventory was compiled and presented in a validation workshop.

3.9. Improvement plan

Energy sector

The following are the main areas of improvement of the inventory in the energy sector:

1) Consistency of the time series for future inventories. The data used regarding fuel consumption comes from different data sources (The Ministry of Mines and energy, the ERIA report and ASEAN database). The most complete, robust and consistent data is available in the ERIA report, which was developed by a group of experts completing the raw data provided by the Ministry of Mines and Energy. Nevertheless, the Ministry of mines and energy has not followed the work made for the ERIA report for year 2016, issue that affects the consistency of the dataset, but it is highlighted in the following sectors*fuels:

o Evolution of biomass consumption in its distinct types, at least firewood, charcoal and biogas. The different aggregation levels provided by ASEAN, ERIA and the Ministry of Mines affects the consistency of the time series of biomass consumption of categories 1A1, 1A2 and 1A4.

o The value of 2016 for transport jet fuel consumption is very high compared to 2015 of ERIA. The same issue happens in category 1A4, regarding the consumption of oil products in the commerce and public services sector.

o The figures for fuel consumption of oil products in the residential sector are not comparable between the Ministry of Mines and ERIA.

2) Sectoral disaggregation of the energy sector. Related to the previous point, the data of

fuel consumption included in the ERIA report contained certain sectoral break down which is useful for the inventory. In the future, it is recommended to try obtaining more data detailed at sectoral level. As a result of the point 1) and 2) above, it is therefore recommended to the Ministry of mines and energy of Cambodia to implement changes in the collection of energy data to provide more accurate and consistent data to the inventory.

113

3) Develop road transport estimates based on data of vehicles*km. This approach will enable to compare the estimates performed using fuel consumption and improve the quality of the inventory.

4) Develop estimates for railway (starting in May 2016), marine navigation and international marine bunkers.

IPPU sector

The following are the main areas of improvement of the inventory in the IPPU sector:

1) Improvement of national statistics on production and consumption of products. The Ministry of Industry have provided some (limited) data on production for years 2012-2016. It would be relevant for the country to address the need of having systematic and robust statistics.

2) Improvement of the estimates of cement production. In this edition of the inventory, there is data available regarding cement and clinker production from the biggest production plant in the country. This has enabled the inventory to apply a tier 2 methodology for this production. Nevertheless, this production plant accounts for 2/3 of the national production, so cement production is not apply a tier 2 entirely (for the whole category). The obtainment of information from the remaining production plants will enable Cambodia to have a full tier 2 methodology or the next inventory edition.

3) Continuation of the methodology of F-gases. Cambodia has made a significant effort for obtaining data on HFC imports. The continuation of this approach will be key for the quality of the inventory of future editions.

4) Improving the completeness of the IPPU sector. The lack of reliable statistics in the country has hampered an appropriate assessment of the completeness of the inventory. Cambodia should address the identification of activities and launch processes for raising new raw data for the inventory.

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AFOLU sector

3.A.1 - Enteric Fermentation

Emissions from enteric fermentation is estimated thanks to a tier 1 methodology, the main expected improvement for future inventories is to shift towards a tier 2 methodology. For this source, IPCC tier 2 is very detailed and leads to a significative improvement in the inventory. Of course, this methodology is based on additional requirements in terms of data collection. The main data needs concern the characterization of animal populations:

• Typical body weight, • Meat yields, • Milk yields, • Type of feeding, etc.

This effort could be led for cattle, buffaloes and swine which are the main productions for Cambodia.

3.A.2 - Manure Management

For manure management tier 1 and tier 2 are based on the same equations. Currently the inventory corresponds to a tier 1 because only default IPCC parameters are used. But It would be possible to implement a tier 2 by using country-specific data for the distribution between the different manure management systems. In particular, data exist on the development of biogas production in small farms, this type of data could be used to modify the current estimate based on default value proposed by IPCC for Asia. Another key element is the time spent by cattle and buffaloes for grazing. Emissions from grazing are significantly different from those in housing and manure storage, it would be a real improvement to use a country specific estimate for the percentage of manure disposed by grazing. For manure management it would be useful to make additional cross checking between the amount of straw produced by rice crops which are mostly used for livestock feeding and bedding and the estimated of solid manure. In the short-term, it is unrealistic to propose country-specific emission factors for manure management because this emission factors are rather difficult to elaborate and present a very high uncertainty. Moreover, this source remains quite low compared to major key categories of agriculture (enteric fermentation, rice cultivation).

3.B - Land

The methodology used for this inventory is completely copied from the work made for the forest reference level (FRL) in the framework of REDD+ program. Indeed, it is better to keep consistent methodologies and results for the different publications of Cambodia. Nevertheless, it is possible to improve both publications in the future. Different elements could be improved in the future.

Completeness could be improved by adding estimates for the following categories:

• Carbon stock changes for mineral soils. This category was not estimated and may represent a very significative work for inventory teams but, it would complete the reporting for this sector.

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• Carbon stock change for dead organic matter (litter and dead wood). Lower impacts are expected from these pools compared to soil, but it is very dependent on forest types.

• Carbon stock changes for harvested wood products.

• Emissions from biomass burning in relation with land use conversions

• Emissions from forest wildfires

• Emissions from mineralization of organic matter in soils

• Emissions from organic soils

Accuracy, could be improved by collecting additional country specific data:

• On areas. Currently two periods (2006-2010 and 2010-2014) are monitored thanks to 3 different maps (2006, 2010, 2014). It is a very good basis for calculating carbon stock changes, but the period remains a bit short to have a complete view on land use changes. Indeed, in the IPCC it is common to use default period of 20 years to use the default parameters for example for soils. Because the covered period is shorter than 20 years, conversion rates are extrapolated for most recent years and for the period before 2006.

• Many references were collected to estimate carbon stocks on the different categories of lands that are monitored by remote sensing. It is very good but cannot be compared to real data coming from a national forest inventory for example. The collection of specific references on forest areas from Cambodia would represent a strong improvement.

Accuracy, could also be improved by applying IPCC tier 1 methodology for biomass in forest areas:

• Currently a tier 2 is applied with the use of a stock change method for biomass in forest. But it would be possible to implement a tier 1 with the use of growth factors and harvested wood, at least for comparison.

• Currently data were collected and offer the possibility to make a complete approach 2 or even approach 3. Currently, the calculation made corresponds to an approach one which means that carbon stocks changes are fully symmetric in the calculations. For example, the losses observed on deforested area are equivalent to the gains on afforested area. Specific calculations could be developed according to the type of changes in the future.

3.C.1 - Biomass burning

Burning of residues is a real concern for rice cultivation. Currently country-specific data was used to estimate the share of the areas where burning of stubble occurs (on the basis of data for 2005-2006). It is already very good, but it only provides a steady estimate although is likely that this type of practice may change overtime. A major improvement would be to monitor this practice with a new survey to estimate the changes since 2005-2006.

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For grassland the current estimate is based on very scarce information. A specific monitoring would be necessary to improve the estimate of activity data for this source.

3.C.2 - Liming

Liming is not covered currently. It would be necessary to collect such information with a survey to estimate the associated emissions.

3.C.3 - Urea application

Urea consumption is not monitored. Data on fertilizers are provided by the Ministry of Commerce since 2002 but this data only concerns the total amount of fertilizers and not the amounts by type of fertilizer. Currently urea consumption was estimated thanks to FAOSTAT data to estimate a proportion of urea in fertilizers. The monitoring of urea and other nitrogenous fertilizers is part of the improvement plan. The related emissions are currently rather low but fertilizer consumption could increase a lot in the future.

3.C.4 - Direct N2O Emissions from managed soils

As mentioned for urea consumption, nitrogen consumption from mineral fertilizer is not known with a lot of accuracy and this estimate could be improved. Nevertheless, the contribution of mineral fertilizers remains quite low compared to the contribution of organic amendments, pasture, and crop residues. It is certainly more important to focus on organic fertilizers and on the management of crop residues to improve the estimate of this source.

3.C.5 - Indirect N2O Emissions from managed soils

This source may represent big amounts of N2O, but it is linked with the other parameters used to estimated direct N2O emission. The main improvement which could be expected concerns the estimate of NH3 volatilisation.

3.C.6 - Indirect N2O Emissions from manure management

This source represents a very small amount of emissions and is based on very uncertain parameters. It does not appear as a priority in the improvement plan.

3.C.7 - Rice cultivations

This category is a major category for Cambodia. Currently the calculation is based on tier 1 methodology from the IPCC but the calculation is made for 24 different types of rice cultivation. It represents a very detailed calculation and could nearly be considered as a tier 2 (some country-specific parameters are used, and the categorization is high). The main improvements that could be led concern the amounts of residues which are incorporated after harvest and the amounts of organic manure which brought to soils. It could be very interesting to collect additional data on the area really irrigated because the current estimates are based on different sources but not on dedicated statistics. Currently, the cultivation period is defined by type but not changing on the period. In practices varieties of rice are improved and the periods of cultivations are becoming shorter. It could be included in the calculations.

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Waste sector

The following are the main areas of improvement of the inventory in the waste sector:

Developing estimates for the rate of waste generation per capita for the entire time series. Currently, the rate used is constant for the entire time series. The rate is likely to be lower in the historical period, but it has not been estimated in this edition.

Improving the information on waste composition. In this inventory edition, different studies have been considered for the choice of activity data. The differences between studies were found to be significative.

Improving the data gathered on waste disposal, including industrial waste disposal. The information used has been gathered by the MoE and includes municipal and industrial waste disposal. Nevertheless, this information is only partial and do not cover the 100% of the scope of the activity. This issue could be improved by obtaining additional data from the remaining landfills and improving the characterization of the waste management sector in the country.

Raise information about incineration of wastes. This activity occurs in the country, but it has not been estimated due to unavailability of data.

Estimate the amount of waste burned in landfills. This has not been estimated in the current edition of the inventory and could raise significantly the emissions of category 4C3 open burning.

Obtain direct information about composting. This activity occurs in the country, but it has been estimated using assumptions.

Improve the data available from the national biodigesters programme. In the current edition of the inventory, the estimation of emissions due to the production of biogas in the residential sector (which is happening thanks to the national biodigester program), has been estimated deriving the activity data (amount of wastes treated), from information on biogas produced. This information could be improved for future inventory editions.

Improve the statistics on population for improving the estimates of open burning and domestic wastewater. The split between urban and rural population is needed for different areas of the inventory. National statistics has changed the definition of rural used, hampering the estimation of a consistent time series. This issue has been solved using the estimates provided by the World bank. In the future, the improvement of this statistics will enhance the quality of the inventory.

Improve the data on discharge types by population fraction, to improve the calculation of domestic wastewater.

Improving national statistic on industrial production. The quality of the IPPU and waste sectors are very affected for the lack of available information on industrial production. In the future, the improvement of this statistics will enhance the quality of the inventory.

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3.10. Reporting tables

This section includes information in tabular format regarding all the emissions calculated in the 2019 edition of the GHG National Inventory.

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Table 116 – Table A - Summary Table

  

Net CO2   CH4  N2O   HFC  PFC  SF6 

Other halogenated gases with CO2 equivalent conversion factors (3) 

Other halogenated gases without CO2 equivalent conversion factors (4 

NOx  CO  NMVOCs SO2 

GREENHOUSE GAS SOURCE AND SINK CATEGORIES 

Gg  CO2 equivalents (Gg)  Gg 

Total national emissions and removals  142137.97   747.87  8.98 371.68

NA, NE, NO

NA, NE, NO 

NA, NE, NO NA, NE, NO 43.43 160.46 45.03 32.61 

1. Energy  8845.29  23.04  0.61                 43.43  160.46  45.03  32.61 

1A. Fuel combustion (sectoral approach)  8845.29  23.04  0.61                 43.43  160.46  45.03  32.61 

1A1. Energy industries  2990.41  10.05  0.05                 9.23  3.47  0.29  25.14 

1A2. Manufacturing industries and construction  672.28  1.13  0.15                 6.95  23.32  11.39  3.12 

1A3. Transport  4993.03  1.21  0.24                 19.61  86.54  8.61  3.25 

1A4. Other sectors  189.57  10.64  0.17                 7.64  47.14  24.73  1.09 

1A5. Non specified  NO  NO  NO                 NO  NO  NO  NO 

1B. Fugitive emissions from fuels  NO  NO  NO                 NO  NO  NO  NO 

1B1. Solid fuels  NO  NO  NO                 NO  NO  NO  NO 

1B2. Oil and natural gas  NO  NO  NO                 NO  NO  NO  NO 

1B3. Other emissions from energy production  NO  NO  NO                 NO  NO  NO  NO 

1C Carbon Dioxide Transport and Storage  NO                       NO  NO  NO  NO 

1C1. Transport of CO2  NO                       NO  NO  NO  NO 

1C2. Injection and Storage  NO                       NO  NO  NO  NO 

2. Industrial processes  1449.46  NA, NE, NO NA, NE, NO 371.68 NA, NE, NO 

NA, NE, NO  NA, NE, NO  NA, NE, NO  NA, NE, NO  NA, NE, NO

NA, NE, NO 

NA, NE, NO 

2A. Mineral products  1420.96  NA  NA                 NE  NE  NE  NE 

2A1 Cement Production  1420.96  NA  NA                 NE  NE  NE  NE 

2A2 Lime Production  NE  NA  NA                 NE  NE  NE  NE 

2A3 Glass Production  NE  NA  NA                 NE  NE  NE  NE 

2A4 Other Process Uses of Carbonates  NE  NA  NA                 NE  NE  NE  NE 

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Net CO2   CH4  N2O   HFC  PFC  SF6 

Other halogenated gases with CO2 equivalent conversion factors (3) 

Other halogenated gases without CO2 equivalent conversion factors (4 

NOx  CO  NMVOCs SO2 

2A5 Other (please specify)  NO  NA  NA                 NE  NE  NE  NE 

2B.  Chemical industry   NO  NO  NO                 NO  NO  NO  NO 

2B1.  Ammonia production  NO  NO  NO                 NO  NO  NO  NO 

2B2.  Nitric acid production   NO  NO  NO                 NO  NO  NO  NO 

2B3.  Adipic acid production  NO  NO  NO                 NO  NO  NO  NO 

2B4. Caprolactam, glyoxal and glyoxylic acid production  NO  NO  NO                 NO  NO  NO  NO 

2B5.  Carbide production  NO  NO  NO                 NO  NO  NO  NO 

2B6. Titanium dioxide production  NO  NO  NO                 NO  NO  NO  NO 

2B7. Soda ash production  NO  NO  NO                 NO  NO  NO  NO 

2B8. Petrochemical and carbon black production  NO  NO  NO                 NO  NO  NO  NO 

2B9. Fluorochemical production           NO  NO  NO  NO  NO  NO  NO  NO  NO 

2B10.  Other (as specified in table 2(I).A‐H)  NO  NO  NO  NO  NO  NO  NO  NO  NO  NO  NO  NO 

2C.  Metal industry  NE, NO  NE, NO  NE, NO                 NE, NO  NE, NO  NE, NO  NE, NO 

2C1.  Iron and steel production  NE  NE  NE                 NE  NE  NE  NE 

2C2.  Ferroalloys production  NO  NO  NO                 NO  NO  NO  NO 

2C3.  Aluminium production  NO  NO  NO     NO           NO  NO  NO  NO 

2C4.  Magnesium production  NO        NO  NO  NO  NO  NO  NO  NO  NO  NO 

2C5. Lead production  NO                       NO  NO  NO  NO 

2C6. Zinc production  NO                       NO  NO  NO  NO 

2C7.  Other (as specified in table 2(I).A‐H)  NO  NO  NO  NO  NO  NO  NO  NO  NO  NO  NO  NO 

2D.  Non‐energy products from fuels and solvent use  28.50  NE  NE                 NE, NO  NE, NO  NE, NO  NE, NO 

2D1.  Lubricant use  28.50                       NE  NE  NE  NE 

2D2.  Paraffin wax use  NE  NE  NE                 NE  NE  NE  NE 

2D3.  Other                           NO  NO  NO  NO 

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Net CO2   CH4  N2O   HFC  PFC  SF6 

Other halogenated gases with CO2 equivalent conversion factors (3) 

Other halogenated gases without CO2 equivalent conversion factors (4 

NOx  CO  NMVOCs SO2 

2E.  Electronics industry  NE     NE  NE, NO  NE, NO  NE, NO  NE, NO  NE, NO  NE, NO  NE, NO  NE, NO  NE, NO 

2E1.  Integrated circuit or semiconductor  NE     NE  NE  NE  NE  NE  NE  NE  NE  NE  NE 

2E2.  TFT flat panel display           NO  NO  NO  NO  NO  NO  NO  NO  NO 

2E3.  Photovoltaics           NO  NO  NO  NO  NO  NO  NO  NO  NO 

2E4.  Heat transfer fluid                                     

2E5.  Other (as specified in table 2(II))  NO  NO  NO  NO  NO  NO  NO  NO  NO  NO  NO  NO 

2F.  Product uses as substitutes for ODS(2)  NA, NO  NA, NO  NA, NO  371.68  NE, NO     NE, NO  NE, NO  NE, NO  NE, NO  NE, NO  NE, NO 

2F1.  Refrigeration and air conditioning  NA  NA  NA  371.50  NE     NE  NE  NE  NE  NE  NE 

2F2.  Foam blowing agents  NA        NE  NE     NE  NE  NE  NE  NE  NE 

2F3.  Fire protection  NA        0.19  NE     NE  NE  NE  NE  NE  NE 

2F4.  Aerosols           NE  NE     NE  NE  NE  NE  NE  NE 

2F5.  Solvents           NE  NE     NE  NE  NE  NE  NE  NE 

2F6.  Other applications  NO  NO  NO  NO  NO     NO  NO  NO  NO  NO  NO 

2G.  Other product manufacture and use  NO  NO  NE  NO  NA, NO  NE, NO  NE, NO  NE, NO  NA  NA  NA  NA 

2G1.  Electrical equipment              NA  NE  NE  NE  NA  NA  NA  NA 

2G2.  SF6 and PFCs from other product use              NO  NO  NO  NO  NA  NA  NA  NA 

2G3.  N2O from product uses        NE                 NA  NA  NA  NA 

2G4.  Other   NO  NO     NO        NO  NO  NA  NA  NA  NA 

2H.  Other (as specified in tables 2(I).A‐H and 2(II))(3)  NA, NO  NA, NO                    NE  NE  NE  NE 

2H1 Pulp and Paper Industry  NA  NA                    NE  NE  NE  NE 

2H2 Food and Beverages Industry  NA  NA                    NE  NE  NE  NE 

2H3 Other (please specify)  NO  NO  NO                 NE  NE  NE  NE 

3 AGRICULTURE, FORESTRY AND OTHER LAND USE  131028.66  645.15  7.56                 NE, NA,NO  NE, NA,NO 

NE, NA,NO 

NE, NA,NO 

3A Livestock     188.86  2.23                 NE  NA  NE  NA 

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Net CO2   CH4  N2O   HFC  PFC  SF6 

Other halogenated gases with CO2 equivalent conversion factors (3) 

Other halogenated gases without CO2 equivalent conversion factors (4 

NOx  CO  NMVOCs SO2 

3A1 Enteric Fermentation     167.54                    NE  NA  NE  NA 

3A2 Manure Management     21.32  2.23                 NE  NA  NE  NA 

3B Land  131011.24  NE  NE                 NA  NA  NA  NA 

3B1 Forest Land  IE  NE  NE                 NA  NA  NA  NA 

3B2 Cropland  IE  NE  NE                 NA  NA  NA  NA 

3B3 Grassland  IE  NE  NE                 NA  NA  NA  NA 

3B4 Wetlands  IE  NE  NE                 NA  NA  NA  NA 

3B5 Settlements  IE  NE  NE                 NA  NA  NA  NA 

3B6 Other Land  IE  NE  NE                 NA  NA  NA  NA 

3C Aggregate Sources and Non‐CO2 Emissions Sources on Land  17.42  456.29  5.33                 NA  NA  NA  NA 

3C1 Biomass Burning  NA  3.37  0.24                 NE  NE  NE  NE 

3C2 Liming  NE                       NA  NA  NA  NA 

3C3 Urea Application  17.42                       NA  NA  NA  NA 

3C4 Direct N2O Emissions from Managed Soils        3.17                 NA  NA  NA  NA 

3C5 Indirect N2O Emissions from Managed Soils        1.36                 NA  NA  NA  NA 

3C6 Indirect N2O Emissions from Manure Management        0.57                 NA  NA  NA  NA 

3C7 Rice Cultivations     452.93  IE                 NA  NA  NA  NA 

3C8 Other (please specify)  NO  NO  NO                 NO  NO  NO  NO 

3D Other  NE,NO  NO  NO  NO  NO  NO  NO  NO  NO  NO  NO  NO 

3D1 Harvested Wood Products  NE                       NO  NO  NO  NO 

3D2 Other (please specify)  NO  NO  NO                 NO NO NO NO 

4 WASTE  814.553  79.678  0.82                 NE  NE  NE  NE 

4A Solid Waste Disposal     53.83  NA                 NE  NE  NE  NE 

4B Biological Treatment of Solid Waste     0.33  0.02                 NE  NE  NE  NE 

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Net CO2   CH4  N2O   HFC  PFC  SF6 

Other halogenated gases with CO2 equivalent conversion factors (3) 

Other halogenated gases without CO2 equivalent conversion factors (4 

NOx  CO  NMVOCs SO2 

4C Incineration and Open Burning of Waste  814.55  9.46  0.14                 NE  NE  NE  NE 

4D Wastewater Treatment and Discharge     16.06  0.66                 NE  NE  NE  NE 

4E Other (please specify)  NO  NO  NO  NO  NO  NO  NO  NO  NO  NO  NO  NO 

5 OTHER  NE, NO  NO  NE, NO  NO  NO  NO  NO  NO  NE, NO  NE, NO  NE, NO  NE, NO 

5A Indirect N2O Emissions from the Atmospheric Deposition of Nitrogen in NOx and NH3        NE                 NE  NE  NE  NE 

5B Other (please specify)  NO  NO  NO  NO  NO  NO  NO  NO  NO  NO  NO  NO 

Memo items (5)                                     

International Bunkers                                     

International Aviation (International Bunkers)  236.49  0.00  0.01                 0.83  94.44  1.50  0.08 

International Water‐borne Transport (International Bunkers)  NE  NE  NE                 NE  NE  NE  NE 

Multilateral Operations  NE  NE  NE                 NE  NE  NE  NE 

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Table 117 – Table B - Short Summary table

  

Net CO2   CH4  N2O   HFC  PFC  SF6 

Other halogenated gases with CO2 equivalent conversion factors (3) 

Other halogenated gases without CO2 equivalent conversion factors (4 

NOx  CO  NMVOCs SO2 

GREENHOUSE GAS SOURCE AND SINK CATEGORIES 

Gg  CO2 equivalents (Gg)  Gg 

Total national emissions and removals   142137.97   747.87   8.98   371.68 NA, NE, NO 

NA, NE, NO  NA, NE, NO NA, NE, NO43.43  160.46  45.03  32.61 

1. Energy  8845.29  23.04  0.61                 43.43  160.46  45.03  32.61 

1A. Fuel combustion (sectoral approach)  8845.29  23.04  0.61                 43.43  160.46  45.03  32.61 

1B. Fugitive emissions from fuels  NO  NO  NO                 NO  NO  NO  NO 

1C Carbon Dioxide Transport and Storage  NO                       NO  NO  NO  NO 

2. Industrial processes  1449.46 NA, NE, NO 

NA, NE, NO  371.68 

NA, NE, NO  NA, NE, NO  NA, NE, NO  NA, NE, NO 

NA, NE, NO 

NA, NE, NO 

NA, NE, NO  NA, NE, NO

2A. Mineral products  1420.96  NA  NA                 NE  NE  NE  NE 

2B.  Chemical industry   NO  NO  NO                 NO  NO  NO  NO 

2C.  Metal industry  NE ,NO  NE, NO  NE, NO                 NE, NO  NE, NO  NE, NO  NE, NO 

2D.  Non‐energy products from fuels and solvent use  28.50  NE  NE                 NE, NO  NE, NO  NE, NO  NE, NO 

2E.  Electronics industry  NE     NE  NE, NO  NE, NO  NE, NO  NE, NO  NE, NO  NE, NO  NE, NO  NE, NO  NE, NO 

2F.  Product uses as substitutes for ODS(2)  NA , NO  NA, NO  NA, NO  371.68  NE, NO     NE, NO  NE, NO  NE, NO  NE, NO  NE, NO  NE, NO 

2G.  Other product manufacture and use  NO  NO  NE  NO  NA, NO  NE, NO  NE, NO  NE, NO  NA  NA  NA  NA 

2H.  Other (as specified in tables 2(I).A‐H and 2(II))(3)  NA ,NO  NA, NO   NA, NO                 NE  NE  NE  NE 

3 AGRICULTURE, FORESTRY AND OTHER LAND USE  131028.66  645.15  7.56                

NE, NA,NO 

NE, NA,NO 

NE, NA,NO  NE, NA,NO 

3A Livestock     188.86  2.23                 NE  NA  NE  NA 

3B Land  131011.24  NE  NE                 NA  NA  NA  NA 

3C Aggregate Sources and Non‐CO2 Emissions Sources on Land  17.42  456.29  5.33                 NA  NA  NA  NA 

3D Other  NE,NO  NO  NO  NO  NO  NO  NO  NO  NO  NO  NO  NO 

4 WASTE  814.553  79.678  0.82                 NE  NE  NE  NE 

125

  

Net CO2   CH4  N2O   HFC  PFC  SF6 

Other halogenated gases with CO2 equivalent conversion factors (3) 

Other halogenated gases without CO2 equivalent conversion factors (4 

NOx  CO  NMVOCs SO2 

4A Solid Waste Disposal     53.83  NA                 NE  NE  NE  NE 

4B Biological Treatment of Solid Waste     0.33  0.02                 NE  NE  NE  NE 

4C Incineration and Open Burning of Waste  814.55  9.46  0.14                 NE  NE  NE  NE 

4D Wastewater Treatment and Discharge     16.06  0.66                 NE  NE  NE  NE 

4E Other (please specify)  NO  NO  NO  NO  NO  NO  NO  NO  NO  NO  NO  NO 

5 OTHER  NE, NO  NO  NE, NO  NO  NO  NO  NO  NO  NE, NO  NE, NO  NE, NO  NE, NO 

5A Indirect N2O Emissions from the Atmospheric Deposition of Nitrogen in NOx and NH3        NE                 NE  NE  NE  NE 

5B Other (please specify)  NO  NO  NO  NO  NO  NO  NO  NO  NO  NO  NO  NO 

Memo items (5)                                     

International Bunkers                                     

International Aviation (International Bunkers)  236.49  0.00  0.01                 0.83  94.44  1.50  0.08 

International Water‐borne Transport (International Bunkers)  NE  NE  NE                 NE  NE  NE  NE 

Multilateral Operations  NE  NE  NE                 NE  NE  NE  NE 

126

Table 118 – CO2 emissions

Emission source 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

1A1 Energy Industries 48.28 48.28 50.64 52.10 57.27 76.05 86.02 85.58 108.35 112.74 145.40 160.39

1A2 Manufacturing Industry

114.84 114.84 114.71 118.20 152.98 148.84 161.50 190.09 173.10 181.93 193.41 220.26

1A3 Transport 1852.05 1852.05 1888.66 1956.78 2131.31 2150.83 1963.09 2164.41 1965.50 1973.21 1986.68 2161.75

1A4 Other 91.55 91.55 93.00 96.25 121.14 127.39 157.36 156.76 173.68 213.15 199.91 217.63

2A1 Cement production NO NO NO NO NO NO NO NO NO NO NO NO

2D1 Lubricants 3.81 3.81 4.11 4.23 2.21 4.44 6.04 2.47 3.82 5.29 5.84 6.41

2F Subst. for ODS NA NA NA NA NA NA NA NA NA NA NA NA

3A Livestock

3B Land 27018.62 27018.62 27018.62 27018.62 27018.62 27018.62 27018.62 27018.62 27018.62 27018.62 27018.62 27018.62

3C

Aggregate sources and non-CO2 emissions sources on land

1.61 1.61 1.17 1.47 2.36 1.65 1.65 1.65 1.65 1.65 1.65 1.65

3D Other

4A Solid waste disposal

4B Biological treatment of solid waste

4C Incineration and Open burning of waste

623.20 639.91 655.58 670.23 683.86 696.60 708.13 735.76 749.41 762.83 745.01 757.52

4D Wastewater treatment and discharge

Total (Gg) 29753.96 29770.67 29826.48 29917.88 30169.75 30224.43 30102.41 30355.34 30194.14 30269.42 30296.52 30544.23Total with FOLU (Gg CO2-

eq) 29753.96 29770.67 29826.48 29917.88 30169.75 30224.43 30102.41 30355.34 30194.14 30269.42 30296.52 30544.23

Total without FOLU (Gg CO2-eq)

2735 2752 2808 2899 3151 3206 3084 3337 3176 3251 3278 3526

127

Table 119 – cont CO2 emissions

Emission source 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

1A1 Energy Industries 160.39 271.13 392.78 575.93 714.72 852.97 895.48 850.04 678.49 1405.28 2503.66 2990.41

1A2 Manufacturing Industry 220.26 235.75 267.84 279.78 543.55 626.92 655.82 640.77 576.59 508.68 384.87 672.28

1A3 Transport 2161.75 2317.23 2502.67 2644.18 2721.59 2838.89 3251.22 3736.99 3755.94 4057.82 4533.51 4993.03

1A4 Other 217.63 234.02 253.79 270.45 296.31 303.95 336.70 278.93 243.42 223.32 189.57 189.57

2A1 Cement production NO NO 52.63 371.26 347.46 370.14 430.89 486.72 507.13 510.49 652.89 1,420.96

2D1 Lubricants 6.41 6.84 7.39 8.07 8.62 8.60 11.67 10.44 11.67 8.60 28.25 28.50

2F Subst. for ODS NA NA NA NA NA NA NA NA NA NA NA NA

3A Livestock

3B Land 27018.62 27018.62 27018.62 27018.62 27018.62 131011.24 131011.24 131011.24 131011.24 131011.24 131011.24 131011.24

3C

Aggregate sources and non-CO2 emissions sources on land

1.65 1.65 1.88 9.99 12.37 29.90 17.42 17.42 17.42 17.42 17.42 17.42

3D Other

4A Solid waste disposal

4B Biological treatment of solid waste

4C Incineration and Open burning of waste

757.52 709.84 719.22 741.89 745.45 753.71 759.55 771.27 788.63 801.00 804.30 814.55

4D Wastewater treatment and discharge

Total (Gg) 30,544.23 30795.08 31216.81 31920.17 32408.69 136796.33 137370.00 137803.82 137590.52 138543.85 140125.72 142137.97

Total with FOLU (Gg CO2-eq) 30,544.23 30795.08 31216.81 31920.17 32408.69 136796.33 137370.00 137803.82 137590.52 138543.85 140125.72 142137.97 Total without FOLU (Gg CO2-

eq) 3,526 3776 4198 4902 5390 5785 6359 6793 6579 7533 9114 11126.73

128

Table 120 – CH4 emissions

Emission source  1994  1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 

1A1  Energy Industries  10.01  10.01 10.74 11.24 14.54 14.55 14.57 14.59 17.04 17.77 14.24 14.06 

1A2  Manufacturing Industry  1.10  1.10 1.14 1.14 1.21 1.19 1.16 1.14 1.07 1.03 1.06 1.03 

1A3  Transport  0.51  0.51 0.53 0.55 0.52 0.57 0.45 0.44 0.45 0.43 0.42 0.46 

1A4  Other   7.83  7.83 8.19 8.26 9.32 9.19 9.03 8.92 9.06 9.00 8.46 8.23 

2A1  Cement production  NA  NA NA NA NA NA NA NA NA NA NA NA 

2D1  Lubricants  NA  NA NA NA NA NA NA NA NA NA NA NA 

2F  Subst. for ODS  NA  NA NA NA NA NA NA NA NA NA NA NA 

3A  Livestock   188.84  194.38 192.93 195.21 187.67 188.51 199.49 191.13 193.75 200.21 206.61 214.17 

3B  Land  NE   NE NE NE NE NE NE NE NE NE NE NE 

3C 

Aggregate sources and non‐CO2 emissions sources on land  186.85  232.00 232.16 236.98 238.93 245.83 242.74 252.35 261.65 280.73 283.88 312.61 

3D  Other   NO   NO NO NO NO NO NO NO NO NO NO NO 

4A  Solid waste disposal  21.57  22.52 23.58 24.65 25.70 26.69 27.74 28.79 30.04 31.46 33.16 35.02 

4B Biological treatment of solid waste  0.21  0.21 0.22 0.23 0.23 0.24 0.25 0.26 0.26 0.27 0.27 0.27 

4C Incineration and Open burning of waste  7.24  7.43 7.61 7.78 7.94 8.09 8.22 8.54 8.70 8.86 8.65 8.79 

4D Wastewater treatment and discharge  11.45  11.83 12.09 12.44 12.78 12.98 13.28 13.89 14.23 14.45 14.20 14.53 

Total (Gg)  435.61  487.84 489.21 498.48 498.84 507.86 516.92 520.04 536.25 564.23 570.95 609.19 

Total with FOLU (Gg CO2‐eq)  10890.33  12195.93 12230.24 12461.89 12471.08 12696.53 12923.06 13001.00 13406.16 14105.65 14273.75 15229.81 

Total without FOLU (Gg CO2‐eq)  10890.33  12195.93 12230.24 12461.89 12471.08 12696.53 12923.06 13001.00 13406.16 14105.65 14273.75 15229.81 

129

Table 121 – Cont. CH4 emissions

Emission source  2005  2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 

1A1  Energy Industries  14.06  13.63 12.87 12.11 11.35 10.59 9.83 9.06 9.43 9.88 10.04 10.05 

1A2  Manufacturing Industry  1.03  0.99 0.97 0.95 0.98 0.85 0.87 0.93 0.99 1.06 1.13 1.13 

1A3  Transport  0.46  0.49 0.53 0.57 0.61 0.64 0.68 0.80 0.81 0.91 1.11 1.21 

1A4  Other   8.23  7.95 9.18 9.47 9.54 9.64 9.94 10.00 9.97 10.50 10.64 10.64 

2A1  Cement production  NA  NA NA NA NA NA NA NA NA NA NA NA 

2D1  Lubricants  NA  NA NA NA NA NA NA NA NA NA NA NA 

2F  Subst. for ODS  NA  NA NA NA NA NA NA NA NA NA NA NA 

3A  Livestock   214.17  224.59 225.69 227.98 230.27 224.70 220.65 217.88 220.54 197.34 188.10 188.86 

3B  Land  NE   NE  NE  NE  NE  NE  NE  NE  NE  NE  NE  NE  

3C 

Aggregate sources and non‐CO2 emissions sources on land  312.61  329.36 345.23 361.34 380.95 402.58 423.41 442.80 443.46 443.51 441.31 456.29 

3D  Other   NO   NO NO NO NO NO NO NO NO NO NO NO 

4A  Solid waste disposal  35.02  36.76 38.12 39.74 41.43 43.09 43.36 43.94 46.44 48.99 51.53 53.83 

4B Biological treatment of solid waste  0.27  0.26 0.27 0.30 0.30 0.32 0.33 0.33 0.31 0.32 0.33 0.33 

4C Incineration and Open burning of waste  8.79  8.24 8.35 8.61 8.65 8.75 8.82 8.95 9.16 9.30 9.34 9.46 

4D Wastewater treatment and discharge  14.53  13.59 13.98 14.39 14.43 14.81 14.91 15.11 15.60 15.74 16.10 16.06 

Total (Gg)  609.19  635.86 655.18 675.45 698.51 715.96 732.79 749.80 756.73 737.55 729.63 747.87 

Total with FOLU (Gg CO2‐eq)  15229.81  15896.43 16379.49 16886.24 17462.81 17899.08 18319.70 18744.92 18918.17 18438.66 18240.74 18696.71 

Total without FOLU (Gg CO2‐eq)  15229.81  15896.43 16379.49 16886.24 17462.81 17899.08 18319.70 18744.92 18918.17 18438.66 18240.74 18696.71 

130

Table 122 – N2O Emissions

Emission sources   1994  1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

1A1  Energy Industries  0.001  0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.002 0.002 0.002 0.002

1A2 Manufacturing Industry  0.147  0.147 0.153 0.152 0.162 0.159 0.155 0.152 0.143 0.138 0.142 0.138

1A3  Transport  0.091  0.091 0.093 0.096 0.106 0.106 0.098 0.109 0.098 0.099 0.099 0.108

1A4  Other   0.088  0.088 0.092 0.092 0.101 0.099 0.097 0.095 0.093 0.091 0.090 0.087

2A1  Cement production  NA  NA  NA  NA  NA  NA  NA  NA  NA  NA  NA  NA 

2D1  Lubricants  NA  NA  NA  NA  NA  NA  NA  NA  NA  NA  NA  NA 

2F  Subst. for ODS  NA  NA  NA  NA  NA  NA  NA  NA  NA  NA  NA  NA 

3A  Livestock   2.18  2.25 2.24 2.27 2.18 2.20 2.32 2.23 2.26 2.34 2.41 2.50

3B  Land  NE  NE NE NE NE NE NE  NE NE NE NE NE

3C 

Aggregate sources and non‐CO2 emissions sources on land  3.89  4.08 4.06 4.11 3.96 4.06 4.31 4.15 4.22 4.40 4.48 4.76

3D  Other   NO  NO NO NO NO NO NO NO NO NO NO NO

4A  Solid waste disposal  NA  NA NA NA NA NA NA NA NA NA NA NA

4B Biological treatment of solid waste  0.012  0.013 0.013 0.014 0.014 0.014 0.015 0.015 0.016 0.016 0.016 0.016

4C Incineration and Open burning of waste  0.108  0.111 0.114 0.116 0.119 0.121 0.123 0.128 0.130 0.132 0.129 0.131

4D Wastewater treatment and discharge  0.287  0.292 0.301 0.310 0.346 0.383 0.421 0.440 0.451 0.473 0.476 0.499

Total (Gg)  6.80  7.07 7.06 7.16 7.00 7.14 7.54 7.33 7.41 7.69 7.84 8.25

Total with FOLU (Gg CO2‐eq)  2027.85  2107.43 2104.22 2134.56 2084.56 2127.90 2245.84 2182.98 2209.12 2292.50 2337.39 2457.67

Total without FOLU (Gg CO2‐eq)  2027.85  2107.43  2104.22  2134.56 2084.56 2127.90 2245.84 2182.98 2209.12 2292.50 2337.39 2457.67

131

Table 123 – Cont N2O Emissions

 Emission sources   2005  2006 2007 2008 2009 2010  2011 2012 2013 2014 2015 2016

1A1  Energy Industries  0.002  0.003 0.004 0.006 0.007 0.008  0.009 0.009 0.007 0.021 0.040 0.046

1A2 Manufacturing Industry  0.138  0.133 0.129 0.127 0.132 0.115  0.118 0.126 0.134 0.143 0.152 0.153

1A3  Transport  0.108  0.116 0.125 0.132 0.136 0.141  0.162 0.184 0.184 0.197 0.217 0.238

1A4  Other   0.087  0.084 0.131 0.167 0.176 0.207  0.240 0.226 0.147 0.166 0.168 0.168

2A1  Cement production  NA  NA NA NA NA NA  NA NA NA NA NA NA

2D1  Lubricants  NA  NA NA NA NA NA  NA NA NA NA NA NA

2F  Subst. for ODS  NA  NA NA NA NA NA  NA NA NA NA NA NA

3A  Livestock   2.50  2.62 2.63 2.66 2.69 2.62  2.58 2.55 2.59 2.32 2.22 2.23

3B  Land  NE  NE NE NE NE NE  NE NE NE NE NE NE

3C 

Aggregate sources and non‐CO2 emissions sources on land  4.76  5.03 5.10 5.31 5.52 5.51  5.68 5.82 6.00 5.39 5.55 5.33

3D  Other   NO  NO NO NO NO NO  NO NO NO NO NO NO

4A  Solid waste disposal  NA  NA NA NA NA NA  NA NA NA NA NA NA

4B Biological treatment of solid waste  0.016  0.016 0.016 0.016 0.017 0.017  0.017 0.018 0.018 0.018 0.019 0.019

4C Incineration and Open burning of waste  0.131  0.123 0.125 0.129 0.129 0.131  0.132 0.134 0.137 0.139 0.139 0.141

4D Wastewater treatment and discharge  0.499  0.470 0.480 0.510 0.524 0.543  0.561 0.582 0.606 0.626 0.640 0.659

Total (Gg)  8.25  8.60 8.74 9.05 9.32 9.30  9.49 9.65 9.83 9.02 9.14 8.98

Total with FOLU (Gg CO2‐eq)  2457.67  2561.74 2604.46 2697.69 2778.62 2770.65  2829.47 2876.47 2927.94 2688.24 2725.11 2675.98

Total without FOLU (Gg CO2‐eq)  2457.67  2561.74 2604.46 2697.69 2778.62 2770.65  2829.47 2876.47 2927.94 2688.24 2725.11 2675.98

132

Table 124 – CO2-eq Emissions

Emission source  1994 1995 1996 1997 1998 1999  2000 2001 2002 2003 2004 2005

1A1  Energy Industries  299 299 319 333 421 440  451 451 535 558 502 512

1A2  Manufacturing Industry  186 186 189 192 232 226  237 264 243 249 262 287

1A3  Transport  1892 1892 1930 1999 2176 2197  2004 2208 2006 2013 2027 2205

1A4  Other   314 314 325 330 384 387  412 408 428 465 438 449

2A1  Cement production  NO NO NO NO NO NO  NO NO NO NO NO NO

2D1  Lubricants  4 4 4 4 2 4  6 2 4 5 6 6

2F  Subst. for ODS   NO NO NO NO NO NO  NO NO NO NO NO 6

3A  Livestock   5371 5530 5490 5557 5342 5367  5679 5443 5518 5702 5882 6,100

3B  Land  27019 27019 27019 27019 27019 27019  27019 27019 27019 27019 27019 27019

3C Aggregate sources and non‐CO2 emissions sources on land  5832 7017 7014 7151 7157 7358  7353 7548 7800 8333 8434 9236

3D  Other   0 0 0 0 0 0  0 0 0 0 0 0

4A  Solid waste disposal  539 563 590 616 643 667  693 720 751 787 829 876

4B  Biological treatment of solid waste  9 9 9 10 10 10  11 11 11 12 11 12

4C Incineration and Open burning of waste  836 859 880 899 918 935  950 987 1006 1024 1000 1017

4D Wastewater treatment and discharge  372 383 392 403 422 439  457 478 490 502 497 512

Total with FOLU  42672 44074 44161 44514 44725 45049  45271 45539 45809 46668 46908 48238

Total without FOLU  15654 17055 17142 17496 17707 18030  18253 18521 18791 19649 19889 21219

133

Table 125 – Cont. CO2-eq Emissions

Emission source  2005 2006 2007 2008 2009 2010  2011 2012 2013 2014 2015 2016

1A1  Energy Industries  512 613 716 880 1001 1120  1144 1079 917 1658 2767 3,256

1A2  Manufacturing Industry  287 300 331 341 607 682  713 701 641 578 458 746

1A3  Transport  2205 2364 2553 2698 2777 2897  3316 3812 3831 4139 4626 5,094

1A4  Other   449 458 522 557 587 607  657 596 536 535 506 506

2A1  Cement production  NO NO 53 371 347 370  431 487 507 510 653 1,421

2D1  Lubricants  6 7 7 8 9 9  12 10 12 9 28 29

2F  Subst. for ODS  6 18 36 57 84 114  148 186 220 262 320 372

3A  Livestock   6100 6396 6426 6491 6557 6400  6285 6207 6286 5625 5363 5,385

3B  Land  27019 27019 27019 27019 27019 131011  131011 131011 131011 131011 131011 131,011

3C Aggregate sources and non‐CO2 emissions sources on land  9236 9734 10153 10626 11180 11736  12295 12823 12892 12711 12706 13,013

3D  Other   0 0 0 0 0 0  0 0 0 0 0 0

4A  Solid waste disposal  876 919 953 994 1036 1077  1084 1099 1161 1225 1288 1,346

4B  Biological treatment of solid waste  12 11 12 12 13 13  13 14 13 14 14 14

4C Incineration and Open burning of waste  1017 953 965 996 1000 1011  1019 1035 1058 1075 1079 1,093

4D Wastewater treatment and discharge  512 480 492 512 517 532  540 551 571 580 593 598

Total with FOLU  48238 49272 50236 51562 52734 157580  158667 159611 159657 159932 161412 163882

Total without FOLU  21219 22253 23218 24543 25715 26569  27656 28600 28646 28921 30401 32871